In their Policy & Internet article, “Politicians and the Policy Agenda: Does Use of Twitter by the U.S. Congress Direct New York Times Content?” Matthew A. Shapiro and Libby Hemphill examine the extent to which he traditional media is influenced by politicians’ Twitter posts. They draw on indexing theory, which states that media coverage and framing of key policy issues will tend to track elite debate. To understand why the newspaper covers an issue and predict the daily New York Times content, it is modelled as a function of all of the previous day’s policy issue areas as well as all of the previous day’s Twitter posts about all of the policy issue areas by Democrats and Republicans.

They ask to what extent are the agenda-setting efforts of members of Congress acknowledged by the traditional media; what, if any, the advantages are for one party over the other, measured by the traditional media’s increased attention; and whether there is any variance across different policy issue areas? They find that Twitter is a legitimate political communication vehicle for US officials, that journalists consider Twitter when crafting their coverage, and that Twitter-based announcements by members of Congress are a valid substitute for the traditional communiqué in journalism, particularly for issues related to immigration and marginalized groups, and issues related to the economy and health care.

We caught up with the authors to discuss their findings:

Ed.: Can you give a quick outline of media indexing theory? Does it basically say that the press reports whatever the elite are talking about? (i.e. that press coverage can be thought of as a simple index, which tracks the many conversations that make up elite debate).

Matthew: Indexing theory, in brief, states that the content of media reports reflects the degree to which elites – politicians and leaders in government in particular – are in agreement or disagreement. The greater the level of agreement or consensus among elites, the less news there is to report in terms of elite conflict. This is not to say that a consensus among elites is not newsworthy; indexing theory conveys how media reporting is a function of the multiple voices that exist when there is elite debate.

Ed.: You say Twitter seemed a valid measure of news indexing (i.e. coverage) for at least some topics. Could it be that the NYT isn’t following Twitter so much as Twitter (and the NYT) are both following something else, i.e. floor debates, releases, etc.?

Matthew: We can’t test for whether the NYT is following Twitter rather than floor debates/press releases without collecting data for the latter. Perhaps If the House and Senate Press Galleries are indexing the news based on House and Senate debates, and if Twitter posts by members of Congress reflect the House and Senate discussions, we could still argue that Twitter remains significant because there are no limits on the amount of discussion – i.e. the boundaries of the House and Senate floors no longer exist – and the media are increasingly reliant on politicians’ use of Twitter to communicate to the press. In any case, the existing research shows that journalists are increasingly relying on Twitter posts for updates from elites.

Ed.: I’m guessing that indexing theory only really works for non-partisan media that follow elite debates, like the NYT? Or does it also work for tabloids? And what about things like Breitbart (and its ilk) .. which I’m guessing appeals explicitly to a populist audience, rather than particularly caring what the elite are talking about?

Matthew: If a study similar to our was done to examine the indexing tendencies of tabloids, Breitbart, or a similar type of media source, the first step would be to determine what is being discussed regularly in these outlets. Assuming, for example, that there isn’t much discussion about marginalized groups in Breitbart, in the context of indexing theory it would not be relevant to examine the pool of congressional Twitter posts mentioning marginalized groups. Those posts are effectively off of Breitbart’s radar. But, generally, indexing theory breaks down if partisanship and bias drive the reporting.

Ed.: Is there any sense in which Trump’s “Twitter diplomacy” has overturned or rendered moot the recent literature on political uses of Twitter? We now have a case where a single (personal) Twitter account can upset the stock market — how does one theorise that?

Matthew: In terms of indexing theory, we could argue that Trump’s Twitter posts themselves generate a response from Democrats and Republicans in Congress and thus muddy the waters by conflating policy issues with other issues like his personality, ties to Russia, his fact-checking problems, etc. This is well beyond our focus in the article, but we speculate that Trump’s early-dawn use of Twitter is primarily for marketing, damage control, and deflection. There are really many different ways to study this phenomenon. One could, for example, examine the function of unfiltered news from politician to the public and compare it with the news that is simultaneously reported in the media. We would also be interested in understanding why Trump and politicians like Trump frame their Twitter posts the way they do, what effect these posts have on their devoted followers as well as their fence-sitting followers, and how this mobilizes Congress both online (i.e. on Twitter) and when discussing and voting on policy options on the Senate and House floors. These areas of research would all build upon rather than render moot the extant literature on the political uses of Twitter.

Ed.: Following on: how does Indexing theory deal with Trump’s populism (i.e. avowedly anti-Washington position), hatred and contempt of the media, and apparent aim of bypassing the mainstream press wherever possible: even ditching the press pool and favouring populist outlets over the NYT in press gaggles. Or is the media bigger than the President .. will indexing theory survive Trump?

Matthew: Indexing theory will of course survive Trump. What we are witnessing in the media is an inability, however, to limit gaper’s block in the sense that the media focus on the more inflammatory and controversial aspects of Trump’s Twitter posts – unfortunately on a daily basis – rather than reporting the policy implications. The media have to report what is news, and Presidential Twitter posts are now newsworthy, but we would argue that we are reaching a point where anything but the meat of the policy implications must be effectively filtered. Until we reach a point where the NYT ignores the inflammatory nature of Trumps Twitter posts, it will be challenging to test indexing theory in the context of the policy agenda setting process.

Ed.: There are recent examples (Brexit, Trump) of the media apparently getting things wrong because they were following the elites and not “the forgotten” (or deplorable) .. who then voted in droves. Is there any sense in the media industry that it needs to rethink things a bit — i.e. that maybe the elite is not always going to be in control of events, or even be an accurate bellwether?

Matthew: This question highlights an omission from our article, namely that indexing theory marginalizes the role of non-elite voices. We agree that the media could do a better job reporting on certain things; for instance, relying extensively on weather vanes of public opinion that do not account for inaccurate self-reporting (i.e. people not accurately representing themselves when being polled about their support for Trump, Brexit, etc.) or understanding why disenfranchised voters might opt to stay home on Election Day. When it comes to setting the policy agenda, which is the focus of our article, we stand by indexing theory given our assumption that the policy process itself is typically directed from those holding power. On that point, and regardless of whether it is normatively appropriate, elites are accurate bellwethers of the policy agenda.

Read the full article: Shapiro, M.A. and Hemphill, L. (2017) Politicians and the Policy Agenda: Does Use of Twitter by the U.S. Congress Direct New York Times Content? Policy & Internet 9 (1) doi:10.1002/poi3.120.

Matthew A. Shapiro and Libby Hemphill were talking to blog editor David Sutcliffe.

However, new social media, including YouTube, provide opportunities for less-mainstream narratives of cooperation. In their Policy & Internet article “Do New Media Support New Policy Narratives? The Social Construction of the U.S.–Mexico Border on YouTube”, Donna L. Lybecker, Mark K. McBeth, Maria A. Husmann, and Nicholas Pelikan find that YouTube videos about the U.S.–Mexico border focus (perhaps unsurprisingly) on mainstream, divisive issues such as security and violence, immigration, and drugs. However, the videos appear to construct more favourable perspectives of the border region than traditional media, with around half constructing a sympathetic view of the border, and the people associated with it.

The common perceptions of the border generally take two distinct forms. One holds the U.S.–Mexico border to be the location of an annual legal flow of economic trade of $300 billion each year, a line which millions of people legally cross annually, the frontier of 100 years of peaceful coexistence between two countries, and the point of integration for the U.S.–Mexico relationship. An alternative perspective (particularly common since 9/11) focuses less on economic trade and legal crossing and more on undocumented immigration, violence and drug wars, and a U.S.-centric view of “us versus them”.

In order to garner public support for their “solutions” to these issues, politicians often define the border using one of these perspectives. Acceptance of the first view might well allow policymakers to find cooperative solutions to joint problems. Acceptance of the second creates a policy problem that is more value-laden than empirically based and that creates distrust and polarization among stakeholders and between the countries. The U.S.–Mexico border is clearly a complex region encompassing both positives and negatives — but understanding these narratives could have a real-world impact on policy along the border; possibly creating the greater cooperation we need to solve many of the urgent problems faced by border communities.

We caught up with the authors to discuss their findings:

Ed.: Who created the videos you studied: were they created by the public, or were they also produced by perhaps more progressive media outlets? i.e. were you able to disentangle the effect of the media in terms of these narratives?

Mark / Donna: For this study, we studied YouTube videos, using the “relevance” filter. Thus, the videos were ordered by most related to our topic and by most frequently viewed. With this selection method we captured videos produced by a variety of sources; some that contained embedded videos from mainstream media, others created by non-profit groups and public television groups, but also videos produced by interested citizens or private groups. The non-profit and media groups more often discuss the beneficial elements of the border (trade, shared environmental protection, etc.), while individual citizens or groups tended to post the more emotional and narrative-driven videos more likely to construct the border residents in a non-deserving sense.

Ed.: How influential do you think these videos are? In a world of extreme media concentration (where even the US President seems to get his news from Fox headlines and the 42 people he follows on Twitter) .. how significant is “home grown” content; which after all may have better, or at least more locally-representative, information than certain parts of the national media?

Mark / Donna: Today’s extreme media world supplies us with constant and fast-moving news. YouTube is part of the media mix, frequently mentioned as the second largest search engine on the web, and as such is influential. Media sources report that a large number of diverse people use YouTube, thus the videos encompass a broad swath of international, domestic and local issues. That said, as with most news sources today, some individuals gravitate to the stories that represent their point of view, and YouTube makes it possible for individuals to do just this. In other words, if a person perceives the US-Mexico border as a horrible place, they can use key words to search YouTube videos that represent that point of view.

However, we believe YouTube to be more influential than some other sources precisely because it encompasses diversity, thus, even when searching using specific terms, there will likely be a few videos included in search results that provide a different point of view. Furthermore, we did find some local, “home grown” content included in search results, again adding to the diversity presented to the individual watching YouTube. Although, we found less homegrown content than initially expected. Overall, there is selectivity bias with YouTube, like any type of media, but YouTube’s greater diversity of postings and viewers and broad distribution may increase both exposure and influence.

Ed.: Your article was published pre-Trump. How do you think things might have changed post-election, particularly given the uncertainty over “the wall“ and NAFTA — and Trump’s rather strident narratives about each? Is it still a case of “negative traditional media; equivocal social media”?

Mark / Donna: Our guess is that anti-border forces are more prominent on YouTube since Trump’s election and inauguration. Unless there is an organized effort to counter discussion of “the wall” and produce positive constructions of the border, we expect that YouTube videos posted over the past few months lean more toward non-deserving constructions.

Ed.: How significant do you think social media is for news and politics generally, i.e. its influence in this information environment — compared with (say) the mainstream press and party-machines? I guess Trump’s disintermediated tweeting might have turned a few assumptions on their heads, in terms of the relation between news, social media and politics? Or is the media always going to be bigger than Trump / the President?

Mark / Donna: Social media, including YouTube and Twitter, is interactive and thus allows anyone to bypass traditional institutions. President Trump can bypass institutions of government, media institutions, even his own political party and staff and communicate directly with people via Twitter. Of course, there are advantages to that, including hearing views that differ from the “official lines,” but there are also pitfalls, such as minimized editing of comments.

We believe people see both the strengths and the weakness with social media, and thus often read news from both traditional media sources and social media. Traditional media is still powerful and connected to traditional institutions, thus, remains a substantial source of information for many people — although social media numbers are climbing, particularly with the President’s use of Twitter. Overall, both types of media influence politics, although we do not expect future presidents will necessarily emulate President Trump’s use of social media.

Ed.: Another thing we hear a lot about now is “filter bubbles” (and whether or not they’re a thing). YouTube filters viewing suggestions according to what you watch, but still presents a vast range of both good and mad content: how significant do you think YouTube (and the explosion of smartphone video) content is in today’s information / media environment? (And are filter bubbles really a thing..?)

Mark / Donna: Yeah, we think that the filter bubbles are real. Again, we think that social media has a lot of potential to provide new information to people (and still does); although currently social media is falling into the same selectivity bias that characterizes the traditional media. We encourage our students to use online technology to seek out diverse sources; sources that both mirror their opinions and that oppose their opinions. People in the US can access diverse sources on a daily basis, but they have to be willing to seek out perspectives that differ from their own view, perspectives other than their favoured news source.

The key is getting individuals to want to challenge themselves and to be open to cognitive dissonance as they read or watch material that differs from their belief systems. Technology is advanced but humans still suffer the cognitive limitations from which they have always suffered. The political system in the US, and likely other places, encourages it. The key is for individuals to be willing to listen to views unlike their own.

Read the full article: Lybecker, D.L., McBeth, M.K., Husmann, M.A, and Pelikan, N. (2015) Do New Media Support New Policy Narratives? The Social Construction of the U.S.–Mexico Border on YouTube. Policy & Internet 7 (4). DOI: 10.1002/poi3.94.

Mark McBeth and Donna Lybecker were talking to blog editor David Sutcliffe.

Attention has focused on echo chambers, with many arguing that social media users exist in ideological filter bubbles, narrowly focused on their own preferences, prey to fake news and political bots, reinforcing polarization and leading voters to turn away from the mainstream. Mark Zuckerberg has responded with the strange claim that his company (built on $5 billion of advertising revenue) does not influence people’s decisions.

So what role did social media play in the political events of 2016?

Political turbulence and the new populism

There is no doubt that social media has brought change to politics. From the waves of protest and unrest in response to the 2008 financial crisis, to the Arab spring of 2011, there has been a generalized feeling that political mobilization is on the rise, and that social media had something to do with it.

Our book investigating the relationship between social media and collective action, Political Turbulence, focuses on how social media allows new, “tiny acts” of political participation (liking, tweeting, viewing, following, signing petitions and so on), which turn social movement theory around. Rather than identifying with issues, forming collective identity and then acting to support the interests of that identity – or voting for a political party that supports it – in a social media world, people act first, and think about it, or identify with others later, if at all.

These tiny acts of participation can scale up to large-scale mobilizations, such as demonstrations, protests or campaigns for policy change. But they almost always don’t. The overwhelming majority (99.99%) of petitions to the UK or US governments fail to get the 100,000 signatures required for a parliamentary debate (UK) or an official response (US).

The very few that succeed do so very quickly on a massive scale (petitions challenging the Brexit and Trump votes immediately shot above 4 million signatures, to become the largest petitions in history), but without the normal organizational or institutional trappings of a social or political movement, such as leaders or political parties – the reason why so many of the Arab Spring revolutions proved disappointing.

This explosive rise, non-normal distribution and lack of organization that characterizes contemporary politics can explain why many political developments of our time seem to come from nowhere. It can help to understand the shock waves of support that brought us the Italian Five Star Movement, Podemos in Spain, Jeremy Corbyn, Bernie Sanders, and most recently Brexit and Trump – all of which have campaigned against the “establishment” and challenged traditional political institutions to breaking point.

Each successive mobilization has made people believe that challengers from outside the mainstream are viable – and that is in part what has brought us unlikely results on both sides of the Atlantic. But it doesn’t explain everything.

We’ve had waves of populism before – long before social media (indeed many have made parallels between the politics of 2016 and that of the 1930s). While claims that social media feeds are the biggest threat to democracy, leading to the “disintegration of the general will” and “polarization that drives populism” abound, hard evidence is more difficult to find.

The myth of the echo chamber

The mechanism that is most often offered for this state of events is the existence of echo chambers or filter bubbles. The argument goes that first social media platforms feed people the news that is closest to their own ideological standpoint (estimated from their previous patterns of consumption) and second, that people create their own personalized information environments through their online behaviour, selecting friends and news sources that back up their world view.

Once in these ideological bubbles, people are prey to fake news and political bots that further reinforce their views. So, some argue, social media reinforces people’s current views and acts as a polarizing force on politics, meaning that “random exposure to content is gone from our diets of news and information”.

Really? Is exposure less random than before? Surely the most perfect echo chamber would be the one occupied by someone who only read the Daily Mail in the 1930s – with little possibility of other news – or someone who just watches Fox News? Can our new habitat on social media really be as closed off as these environments, when our digital networks are so very much larger and more heterogeneous than anything we’ve had before?

Research suggests not. A recent large-scale survey (of 50,000 news consumers in 26 countries) shows how those who do not use social media on average come across news from significantly fewer different online sources than those who do. Social media users, it found, receive an additional “boost” in the number of news sources they use each week, even if they are not actually trying to consume more news. These findings are reinforced by an analysis of Facebook data, where 8.8 billion posts, likes and comments were posted through the US election.

Recent research published in Science shows that algorithms play less of a role in exposure to attitude-challenging content than individuals’ own choices and that “on average more than 20% of an individual’s Facebook friends who report an ideological affiliation are from the opposing party”, meaning that social media exposes individuals to at least some ideologically cross-cutting viewpoints: “24% of the hard content shared by liberals’ friends is cross-cutting, compared to 35% for conservatives” (the equivalent figures would be 40% and 45% if random).

In fact, companies have no incentive to create hermetically sealed (as I have heard one commentator claim) echo chambers. Most of social media content is not about politics (sorry guys) – most of that £5 billion advertising revenue does not come from political organizations. So any incentives that companies have to create echo chambers – for the purposes of targeted advertising, for example – are most likely to relate to lifestyle choices or entertainment preferences, rather than political attitudes.

And where filter bubbles do exist they are constantly shifting and sliding – easily punctured by a trending cross-issue item (anybody looking at #Election2016 shortly before polling day would have seen a rich mix of views, while having little doubt about Trump’s impending victory).

And of course, even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach.

And from the research, it looks like they managed to do just that. A barrage of evidence suggests that such advertising was effective in the 2015 UK general election (where the Conservatives spent 10 times as much as Labour on Facebook advertising), in the EU referendum (where the Leave campaign also focused on paid Facebook ads) and in the presidential election, where Facebook advertising has been credited for Trump’s victory, while the Clinton campaign focused on TV ads. And of course, advanced advertising techniques might actually focus on those undecided voters from their conversations. This is not the bottom-up political mobilization that fired off support for Podemos or Bernie Sanders. It is massive top-down advertising dollars.

Ironically however, these huge top-down political advertising campaigns have some of the same characteristics as the bottom-up movements discussed above, particularly sustainability. Former New York Governor Mario Cuomo’s dictum that candidates “campaign in poetry and govern in prose” may need an update. Barack Obama’s innovative campaigns of online social networks, micro-donations and matching support were miraculous, but the extent to which he developed digital government or data-driven policy-making in office was disappointing. Campaign digitally, govern in analogue might be the new mantra.

Chaotic pluralism

Politics is a lot messier in the social media era than it used to be – whether something takes off and succeeds in gaining critical mass is far more random than it appears to be from a casual glance, where we see only those that succeed.

In Political Turbulence, we wanted to identify the model of democracy that best encapsulates politics intertwined with social media. The dynamics we observed seem to be leading us to a model of “chaotic pluralism”, characterized by diversity and heterogeneity – similar to early pluralist models – but also by non-linearity and high interconnectivity, making liberal democracies far more disorganized, unstable and unpredictable than the architects of pluralist political thought ever envisaged.

Perhaps rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

Within chaotic pluralism, there is an urgent need for redesigning democratic institutions that can accommodate new forms of political engagement, and respond to the discontent, inequalities and feelings of exclusion – even anger and alienation – that are at the root of the new populism. We should be using social media to listen to (rather than merely talk at) the expression of these public sentiments, and not just at election time.

Many political institutions – for example, the British Labour Party, the US Republican Party, and the first-past-the-post electoral system shared by both countries – are in crisis, precisely because they have become so far removed from the concerns and needs of citizens. Redesign will need to include social media platforms themselves, which have rapidly become established as institutions of democracy and will be at the heart of any democratic revival.

As these platforms finally start to admit to being media companies (rather than tech companies), we will need to demand human intervention and transparency over algorithms that determine trending news; factchecking (where Google took the lead); algorithms that detect fake news; and possibly even “public interest” bots to counteract the rise of computational propaganda.

Meanwhile, the only thing we can really predict with certainty is that unpredictable things will happen and that social media will be part of our political future.

Discussing the echoes of the 1930s in today’s politics, the Wall Street Journal points out how Roosevelt managed to steer between the extremes of left and right because he knew that “public sentiments of anger and alienation aren’t to be belittled or dismissed, for their causes can be legitimate and their consequences powerful”. The path through populism and polarization may involve using the opportunity that social media presents to listen, understand and respond to these sentiments.

This piece draws on research from Political Turbulence: How Social Media Shape Collective Action (Princeton University Press, 2016), by Helen Margetts, Peter John, Scott Hale and Taha Yasseri.

It is cross-posted from the World Economic Forum, where it was first published on 22 December 2016.

Greg: As I explain in the article, there is a common belief that mass media outlets, and especially online mass media outlets, often portray government in a negative light in an effort to pique the interest of readers. This tendency of media outlets to engage in ‘bureaucracy bashing’ is thought, in turn, to detract from the public’s support for their government. The basic assumption underpinning this relationship is that the more negative information on government there is, the more negative public opinion. However, in my analyses, I found evidence of a positive indirect relationship between citizens’ use of online mass media outlets and their levels of trust in government. Interestingly, however, the more frequently citizens used online mass media outlets for information about their government, the weaker this association became. These findings challenge conventional wisdom that suggests greater exposure to mass media outlets will result in more negative perceptions of the public sector.

Ed: So you find that that the particular positive or negative spin of the actual message may not be as important as the individuals’ sense that they are aware of the activities of the public sector. That’s presumably good news — both for government, and for efforts to ‘open it up’?

Greg: Yes, I think it can be. However, a few important caveats apply. First, the positive relationship between online mass media use and perceptions of government tapers off as respondents made more frequent use of online mass media outlets. In the study, I interpreted this to mean that exposure to mass media had less of an influence upon those who were more aware of public affairs, and more of an influence upon those who were less aware of public affairs. Therefore, there is something of a diminishing returns aspect to this relationship. Second, this study was not able to account for the valence (ie how positive or negative the information is) of information respondents were exposed to when using online mass media. While some attempts were made to control for valance by adding different control variables, further research drawing upon experimental research designs would be useful in substantiating the relationship between the valence of information disseminated by mass media outlets and citizens’ perceptions of their government.

Ed: Do you think governments are aware of this relationship — ie that an indirect effect of being more open and present in the media, might be increased citizen trust — and that they are responding accordingly?

Greg: I think that there is a general idea that more communication is better than less communication. However, at the same time there is a lot of evidence to suggest that some of the more complex aspects of the relationship between openness and trust in government go unaccounted for in current attempts by public sector organizations to become more open and transparent. As a result, this tool that public organizations have at their disposal is not being used as effectively as it could be, and in some instances is being used in ways that are counterproductive–that is, actually decreasing citizen trust in government. Therefore, in order for governments to translate greater openness into greater trust in government, more refined applications are necessary.

Ed: I know there are various initiatives in the UK — open government data / FoIs / departmental social media channels etc. — aimed at a general opening up of government processes. How open is the Korean government? Is a greater openness something they might adopt (or are adopting?) as part of a general aim to have a more informed and involved — and therefore hopefully more trusting — citizenry?

Greg: The South Korean Government, as well as the Seoul Metropolitan Government have gone to great lengths to enhance their openness. Their strategy has made use of different ICTs, such as e-government websites, social media accounts, non-emergency call centers, and smart phone apps. As a result, many now say that attempts by the Korean Government to become more open are more advanced than in many other areas of the developed world. However, the persistent issue in South Korea, as elsewhere, is whether these attempts are having the intended impact. A lot of empirical research has found, for example, that various attempts at becoming more open by many governments around the world have fallen short of creating a more informed and involved citizenry.

Ed: Finally — is there much empirical work or data in this area?

Greg: While there is a lot of excellent empirical research from the field of political science that has examined how mass media use relates to citizens’ perceptions of politicians, political preferences, or their levels of political knowledge, this topic has received almost no attention at all in public management/administration. This lack of discussion is surprising, given mass media has long served as a key means of enhancing the transparency and accountability of public organizations.

Read the full article: Porumbescu, G. (2013) Assessing the Link Between Online Mass Media and Trust in Government: Evidence From Seoul, South Korea. Policy & Internet 5 (4) 418-443.

Greg Porumbescu was talking to blog editor David Sutcliffe.

Gregory Porumbescu is an Assistant Professor at the Northern Illinois University Department of Public Administration. His research interests primarily relate to public sector applications of information and communications technology, transparency and accountability, and citizens’ perceptions of public service provision.

When Jike, the Chinese state-run search engine, launched in 2011, its efforts received a mixed response. The Chinese government pulled out all the stops to promote it, including placing Deng Yaping, one of China’s most successful athletes at the helm. Jike strategically branded itself as friendly, high-tech, and patriotic to appeal to national pride, competition, and trust. It also signaled a serious attempt by a powerful authoritarian state to nationalize the Internet within its territory, and to extend its influence in the digital sphere. However, plagued by technological inferiority, management deficiencies, financial woes and user indifference, Jike failed in terms of user adoption, pointing to the limits of state influence in the marketplace.

Users and critics remain skeptical of state-run search engines. While some news outlets referred to Jike as “the little search engine that couldn’t,” Chinese propaganda was busy at work rebranding, recalibrating, and reimagining its efforts. The result? The search engine formally known as Jike has now morphed into a new enterprise known as “ChinaSo”. This transformation is not new — Jike originally launched in 2010 under the name Goso, rebranding itself as Jike a year later. The March 2014 unveiling of ChinaSo was the result of the merging of the two state-run search engines Jike and Panguso.

Only time will tell if this new (ad)venture will prove more fruitful. However, several things are worthy of note here. First, despite repeated trials, the Chinese state has not given up on its efforts to expand its digital toolbox and weave a ‘China Wide Web’. Rather, state media have pooled their resources to make their collective, strategic bets. The merging of Jike and Panguso into ChinaSo was backed by several state media giants, including People’s Daily, Xinhua News Agency, and China Central Television. Branded explicitly as “China Search: Authoritative National Search,” ChinaSo reinforces a sense of national identity. How does it perform? ChinaSo now ranks 225th in China and 2139th globally (Alexa.com, 8 February 2015), up from Jike’s ranking of 376th in China and 3,174th globally that we last recorded in May 2013. While ChinaSo’s rankings have increased over time, a low adoption rate continues to haunt the state search engine. Compared to China’s homegrown commercial search giant Baidu that ranks first in China and fifth globally (Alexa.com, 8 February 2015), ChinaSo has a long way to go.

Second, in terms of design, ChinaSo has adopted a mixture of general and vertical search to increase its appeal to a wide range of potential users. Its general search, similar to Google’s and Baidu’s, allows users to query through a search box to receive results in a combination of text, image and video formats based on ChinaSo’s search engine that archives, ranks, and presents information to users. In addition, ChinaSo incorporates vertical search focusing on a wide range of categories such as transportation, investment, education and technology, health, food, tourism, shopping, real estate and cars, and sports and entertainment. Interestingly, ChinaSo also guides searchers by highlighting “top search topics today” as users place their cursor in the search box. Currently, various “anti-corruption” entries appear prominently which correspond to the central government’s high-profile anti-corruption campaigns. Given the opaqueness of search engine operation, it is unclear whether the “top searches” are ChinaSo’s editorial choices or search terms based on user queries. We suspect ChinaSo strategically prioritizes this list to direct user attention.

Third, besides improved functionality that enhances ChinaSo’s priming and agenda-setting abilities, it continues to practice (as did Jike) sophisticated information filtering and presentation. For instance, a search of “New York Times” returns not a single result directing users to the paper’s website — as it is banned in China. Instead, on the first page of results, ChinaSo directs users to several Chinese online encyclopedia entries for New York Times, stock information of NYT, and sanctioned news stories relating to the NYT that have appeared in such official media outlets as People’s Net, China Daily, and Global Times. All information appears in Chinese, which has acted as a natural barrier to the average Chinese user who seeks information outside China. Although Chinese language versions of foreign new organizations such as NYT Chinese, WSJ Chinese, and BBC Chinese exist, they are invariably blocked in China.

Last, ChinaSo’s long-term impact on China’s search market and users remains unclear. While many believe ChinaSo to be a “waste of taxpayer money” due to its persistent inability to carve out its market share in competition, others are willing to give it a shot, especially with regard to queries for official policies and statements, remarking that “[there] is nothing wrong with creating a state-run search engine service” and that ChinaSo’s results are better than those of its commercial counterparts. It seems that users either do not care or remain largely unaware of the surveillance capacities of search engines. Although recent scholarship (for instance here and here) has started to probe the Chinese notion and practices of privacy in social networking sites, no research has been conducted with regard to search-related privacy concerns in the Chinese context.

The idea of a state-sponsored search engine is not new, however. As early as 2005, a few European countries proposed a Euro-centric search engine “Project Quaero” to compete against Google and Yahoo! in what was perceived to be the “threat of Anglo-Saxon cultural imperialism.” In the post-Snowden world, not only are powerful authoritarian countries—China, Russia, Iran, and Turkey—interested in building their own national search engines, democratic countries like Germany and Brazil have also condemned the U.S. government and vowed to create their own “national Internets.”

The changing international political landscape compels researchers, policy makers and the public to re-evaluate previous assumptions of internationalism and confront the reality of the role of the Internet as an extension of state power and national identity instead. In the near future, the “the return of the state”, reflected in various trends to re-nationalize communication networks, will likely go hand in hand with social, economic and cultural changes that cross national and international borders. ChinaSo is part and parcel of the “geopolitical turn” in policy and Internet studies that should command more scholarly and public attention.

Read the full article: Jiang, M. & Okamoto, K. (2014) National identity, ideological apparatus, or panopticon? A case study of the Chinese national search engine Jike. Policy and Internet 6 (1) 89-107.

Min Jiang is an Associate Professor, in the department of Communication Studies, UNC Charlotte. Kristen Okamoto is a Ph.D. Student in the school of Communication Studies, University of Ohio.

Ed: How easy is it to request or scrape data from the “Chinese Web”? And how much of it is under some form of government control?

Han-Teng: Access to data from the Chinese Web, like other Web data, depends on the policies of platforms, the level of data openness, and the availability of data intermediary and tools. All these factors have direct impacts on the quality and usability of data. Since there are many forms of government control and intentions, increasingly not just the websites inside mainland China under Chinese jurisdiction, but also the Chinese “soft power” institutions and individuals telling the “Chinese story” or “Chinese dream” (as opposed to “American dreams”), it requires case-by-case research to determine the extent and level of government control and interventions. Based on my own research on Chinese user-generated encyclopaedias and Chinese-language twitter and Weibo, the research expectations seem to be that control and intervention by Beijing will be most likely on political and cultural topics, not likely on economic or entertainment ones.

This observation is linked to how various forms of government control and interventions are executed, which often requires massive data and human operations to filter, categorise and produce content that are often based on keywords. It is particularly true for Chinese websites in mainland China (behind the Great Firewall, excluding Hong Kong and Macao), where private website companies execute these day-to-day operations under the directives and memos of various Chinese party and government agencies.

Of course there is some extra layer of challenges if researchers try to request content and traffic data from the major Chinese websites for research, especially regarding censorship. Nonetheless, since most Web content data is open, researchers such as Professor Fu in Hong Kong University manage to scrape data sample from Weibo, helping researchers like me to access the data more easily. These openly collected data can then be used to measure potential government control, as has been done for previous research on search engines (Jiang and Akhtar 2011; Zhu et al. 2011) and social media (Bamman et al. 2012; Fu et al. 2013; Fu and Chau 2013; King et al. 2012; Zhu et al. 2012).

It follows that the availability of data intermediary and tools will become important for both academic and corporate research. Many new “public opinion monitoring” companies compete to provide better tools and datasets as data intermediaries, including the Online Public Opinion Monitoring and Measuring Unit (人民网舆情监测室) of the People’s Net (a Party press organ) with annual revenue near 200 million RMB. Hence, in addition to the on-going considerations on big data and Web data research, we need to factor in how these private and public Web data intermediaries shape the Chinese Web data environment (Liao et al. 2013).

Given the fact that the government’s control of information on the Chinese Web involves not only the marginalization (as opposed to the traditional censorship) of “unwanted” messages and information, but also the prioritisation of propaganda or pro-government messages (including those made by paid commentators and “robots”), I would add that the new challenges for researchers include the detection of paid (and sometimes robot-generated) comments. Although these challenges are not exactly the same as data access, researchers need to consider them for data collection.

Ed: How much of the content and traffic is identifiable or geolocatable by region (eg mainland vs Hong Kong, Taiwan, abroad)?

Han-Teng: Identifying geographic information from Chinese Web data, like other Web data, can be largely done by geo-IP (a straightforward IP to geographic location mapping service), domain names (.cn for China; .hk for Hong Kong; .tw for Taiwan), and language preferences (simplified Chinese used by mainland Chinese users; traditional Chinese used by Hong Kong and Taiwan). Again, like the question of data access, the availability and quality of such geographic and linguistic information depends on the policies, openness, and the availability of data intermediary and tools.

Nonetheless, there exist research efforts on using geographic and/or linguistic information of Chinese Web data to assess the level and extent of convergence and separation of Chinese information and users around the world (Etling et al. 2009; Liao 2008; Taneja and Wu 2013). Etling and colleagues (2009) concluded their mapping of Chinese blogsphere research with the interpretation of five “attentive spaces” roughly corresponding to five clusters or zones in the network map: on one side, two clusters of “Pro-state” and “Business” bloggers, and on the other, two clusters of “Overseas” bloggers (including Hong Kong and Taiwan) and “Culture”. Situated between the three clusters of “Pro-state”, “Overseas” and “Culture” (and thus at the centre of the network map) is the remaining cluster they call the “critical discourse” cluster, which is at the intersection of the two sides (albeit more on the “blocked” side of the Great Firewall).

I myself found distinct geographic focus and linguistic preferences between the online citations in Baidu Baike and Chinese Wikipedia (Liao 2008). Other research based on a sample of traffic data shows the existence of a “Chinese” cluster as an instance of a “culturally defined market”, regardless of their geographic and linguistic differences (Taneja and Wu 2013). Although I found their argument that the Great Firewall has very limited impacts on such a single “Chinese” cluster, they demonstrate the possibility of extracting geographic and linguistic information on Chinese Web data for better understanding the dynamics of Chinese online interactions; which are by no means limited within China or behind the Great Firewall.

Ed: In terms of online monitoring of public opinion, is it possible to identify robots / “50 cent party” — that is, what proportion of the “opinion” actually has a government source?

Han-Teng: There exist research efforts in identifying robot comments by analysing the patterns and content of comments, and their profile relationship with other accounts. It is more difficult to prove the direct footprint of government sources. Nonetheless, if researchers take another approach such as narrative analysis for well-defined propaganda research (such as the pro- and anti-Falun opinions), it might be easier to categorise and visualise the dynamics and then trace back to the origins of dominant keywords and narratives to identify the sources of loud messages. I personally think such research and analytical efforts require deep knowledge on both technical and cultural-political understanding of Chinese Web data, preferably with an integrated mixed method research design that incorporates both the quantitative and qualitative methods required for the data question at hand.

Ed: In terms of censorship, ISPs operate within explicit governmental guidelines; do the public (who contribute content) also have explicit rules about what topics and content are ‘acceptable’, or do they have to work it out by seeing what gets deleted?

Han-Teng: As a general rule, online censorship works better when individual contributors are isolated. Most of the time, contributors experience technical difficulties when using Beijing’s unwanted keywords or undesired websites, triggering self-censorship behaviours to avoid such difficulties. I personally believe such tacit learning serves as the most relevant psychological and behaviour mechanism (rather than explicit rules). In a sense, the power of censorship and political discipline is the fact that the real rules of engagement are never explicit to users, thereby giving more power to technocrats to exercise power in a more arbitrary fashion. I would describe the general situation as follows. Directives are given to both ISPs and ICPs about certain “hot terms”, some dynamic and some constant. Users “learn” them through encountering various forms of “technical difficulties”. Thus, while ISPs and ICPs may not enforce the same directives in the same fashion (some overshoot while others undershoot), the general tacit knowledge about the “red line” is thus delivered.

Nevertheless, there are some efforts where users do share their experiences with one another, so that they have a social understanding of what information and which category of users is being disciplined. There are also constant efforts outside mainland China, especially institutions in Hong Kong and Berkeley to monitor what is being deleted. However, given the fact that data is abundant for Chinese users, I have become more worried about the phenomenon of “marginalization of information and/or narratives”. It should be noted that censorship or deletion is just one of the tools of propaganda technocrats and that the Chinese Communist Party has had its share of historical lessons (and also victories) against its past opponents, such as the Chinese Nationalist Party and the United States during the Chinese Civil War and the Cold War. I strongly believe that as researchers we need better concepts and tools to assess the dynamics of information marginalization and prioritisation, treating censorship and data deletion as one mechanism of information marginalization in the age of data abundance and limited attention.

Ed: Has anyone tried to produce a map of censorship: ie mapping absence of discussion? For a researcher wanting to do this, how would they get hold of the deleted content?

Han-Teng: Mapping censorship has been done through experiment (MacKinnon 2008; Zhu et al. 2011) and by contrasting datasets (Fu et al. 2013; Liao 2013; Zhu et al. 2012). Here the availability of data intermediaries such as the WeiboScope in Hong Kong University, and unblocked alternative such as Chinese Wikipedia, serve as direct and indirect points of comparison to see what is being or most likely to be deleted. As I am more interested in mapping information marginalization (as opposed to prioritisation), I would say that we need more analytical and visualisation tools to map out the different levels and extent of information censorship and marginalization. The research challenges then shift to the questions of how and why certain content has been deleted inside mainland China, and thus kept or leaked outside China. As we begin to realise that the censorship regime can still achieve its desired political effects by voicing down the undesired messages and voicing up the desired ones, researchers do not necessarily have to get hold of the deleted content from the websites inside mainland China. They can simply reuse plenty of Chinese Web data available outside the censorship and filtering regime to undertake experiments or comparative study.

Ed: What other questions are people trying to explore or answer with data from the “Chinese Web”? And what are the difficulties? For instance, are there enough tools available for academics wanting to process Chinese text?

Han-Teng: As Chinese societies (including mainland China, Hong Kong, Taiwan and other overseas diaspora communities) go digital and networked, it’s only a matter of time before Chinese Web data becomes the equivalent of English Web data. However, there are challenges in processing Chinese language texts, although several of the major challenges become manageable as digital and network tools go multilingual. In fact, Chinese-language users and technologies have been the major goal and actors for a multi-lingual Internet (Liao 2009a,b). While there is technical progress in basic tools, we as Chinese Internet researchers still lack data and tool intermediaries that are designed to process Chinese texts smoothly. For instance, many analytical software and tools depend on or require the use of space characters as word boundaries, a condition that does not apply to Chinese texts.

In addition, since there exist some technical and interpretative challenges in analysing Chinese text datasets with mixed scripts (e.g. simplified and traditional Chinese) or with other foreign languages. Mandarin Chinese language is not the only language inside China; there are indications that the Cantonese and Shanghainese languages have a significant presence. Minority languages such as Tibetan, Mongolian, Uyghur, etc. are also still used by official Chinese websites to demonstrate the cultural inclusiveness of the Chinese authorities. Chinese official and semi-official diplomatic organs have also tried to tell “Chinese stories” in various of the world’s major languages, sometimes in direct competition with its political opponents such as Falun Gong.

These areas of the “Chinese Web” data remain unexplored territory for systematic research, which will require more tools and methods that are similar to the toolkits of multi-lingual Internet researchers. Hence I would say the basic data and tool challenges are not particular to the “Chinese Web”, but are rather a general challenge to the “Web” that is becoming increasingly multilingual by the day. We Chinese Internet researchers do need more collaboration when it comes to sharing data and tools, and I am hopeful that we will have more trustworthy and independent data intermediaries, such as Weiboscope and others, for a better future of the Chinese Web data ecology.

References

Bamman, D., O’Connor, B., & Smith, N. (2012). Censorship and deletion practices in Chinese social media. First Monday, 17(3-5).

Etling, B., Kelly, J., & Faris, R. (2009). Mapping Chinese Blogosphere. In 7th Annual Chinese Internet Research Conference (CIRC 2009). Annenberg School for Communication, University of Pennsylvania, Philadelphia, US.

Fu, K., Chan, C., & Chau, M. (2013). Assessing Censorship on Microblogs in China: Discriminatory Keyword Analysis and Impact Evaluation of the “Real Name Registration” Policy. IEEE Internet Computing, 17(3), 42–50.

Fu, K., & Chau, M. (2013). Reality Check for the Chinese Microblog Space: a random sampling approach. PLOS ONE, 8(3), e58356.

Jiang, M., & Akhtar, A. (2011). Peer into the Black Box of Chinese Search Engines: A Comparative Study of Baidu, Google, and Goso. Presented at the The 9th Chinese Internet Research Conference (CIRC 2011), Washington, D.C.: Institute for the Study of Diplomacy. Georgetown University.

King, G., Pan, J., & Roberts, M. (2012). How censorship in China allows government criticism but silences collective expression. In APSA 2012 Annual Meeting Paper.

Liao, H.-T. (2008). A webometric comparison of Chinese Wikipedia and Baidu Baike and its implications for understanding the Chinese-speaking Internet. In 9th annual Internet Research Conference: Rethinking Community, Rethinking Place. Copenhagen.

Liao, H.-T. (2009a). Are Chinese characters not modern enough? An essay on their role online. GLIMPSE: the art + science of seeing, 2(1), 16–24.

Liao, H.-T. (2009b). Conflict and Consensus in the Chinese version of Wikipedia. IEEE Technology and Society Magazine, 28(2), 49–56. doi:10.1109/MTS.2009.932799

Liao, H.-T. (2013, August 5). How do Baidu Baike and Chinese Wikipedia filter contribution? A case study of network gatekeeping. To be presented at the Wikisym 2013: The Joint International Symposium on Open Collaboration, Hong Kong.

Liao, H.-T., Fu, K., Jiang, M., & Wang, N. (2013, June 15). Chinese Web Data: Definition, Uses, and Scholarship. (Accepted). To be presented at the 11th Annual Chinese Internet Research Conference (CIRC 2013), Oxford, UK.

MacKinnon, R. (2008). Flatter world and thicker walls? Blogs, censorship and civic discourse in China. Public Choice, 134(1), 31–46. doi:10.1007/s11127-007-9199-0

Taneja, H., & Wu, A. X. (2013). How Does the Great Firewall of China Affect Online User Behavior? Isolated “Internets” as Culturally Defined Markets on the WWW. Presented at the 11th Annual Chinese Internet Research Conference (CIRC 2013), Oxford, UK.

Zhu, T., Bronk, C., & Wallach, D. S. (2011). An Analysis of Chinese Search Engine Filtering. arXiv:1107.3794.

Zhu, T., Phipps, D., Pridgen, A., Crandall, J. R., & Wallach, D. S. (2012). Tracking and Quantifying Censorship on a Chinese Microblogging Site. arXiv:1211.6166.

Han-Teng was talking to blog editor David Sutcliffe.

Han-Teng Liao is an OII DPhil student whose research aims to reconsider the role of keywords (as in understanding “keyword advertising” using knowledge from sociolinguistics and information science) and hyperlinks (webometrics) in shaping the sense of “fellow users” in digital networked environments. Specifically, his DPhil project is a comparative study of two major user-contributed Chinese encyclopedias, Chinese Wikipedia and Baidu Baike.

If you have ever worried about media bias then you should really worry about the impact of translation. Before the revolutions, the translation software for Egyptian Arabic was almost non-existent. Few translation applications were able to handle the different Arabic dialects or supply coding labor and capital to build something that could contend with internet blackouts. Google’s Speak to Tweet became the dominant application used in the Egyptian uprisings, delivering one homogenized source of information that fed the other sources. In 2011, this collaboration helped circumvent the problem of Internet connectivity in Egypt by allowing cellphone users to call their tweet into a voicemail to be transcribed and translated. A crowd of volunteers working for Twitter enhanced translation of Egyptian Arabic after the Tweets were first transcribed by a Mechanical Turk application trained from an initial 10 hours of speech.

The unintended consequence of these crowdsourcing applications was that when the material crossed the language barrier into English, it often became inaccessible to the original contributors. Individuals on the ground essentially ceded authorship to crowds of untrained volunteer translators who stripped the information of context, and then plotted it in categories and on maps without feedback from original sources. Controlling the application meant controlling the information flow, the lens through which the revolutions were conveyed to the outside world.

This flawed system prevented the original sources (e.g. in Libya) from interacting with the information that directly related to their own life-threatening situation, while the information became an unsound basis for decision-making by international actors. As Stottlemyre describes, ceding authorship was sometimes an intentional strategy, but also one imposed by the nature of the language/power imbalance and the failure of the translation applications and the associated projects to incorporate feedback loops or more two-way communication.

The after action report for the Libya Crisis Map project commissioned by the UN OCHA offers some insight into the disenfranchisement of sources to the decision-making process once they had provided information for the end product; the crisis map. In the final ‘best practices section’ reviewing the outcomes, The Standby Task Force which created the map described decision-makers and sources, but did not consider or mention the sources’ access to decision-making, the map, or a mechanism by which they could feed back to the decision-making chain. In essence, Libyans were not seen as part of the user group of the product they helped create.

How exactly does translation and crowdsourcing shape our understanding of complex developing crises, or influence subsequent policy decisions?  The SMS polling initiative launched by Al Jazeera English in collaboration with Ushahidi, a prominent crowdsourcing platform, illustrates the most common process of visualizing crisis information: translation, categorization, and mapping.  In December 2011, Al Jazeera launched Somalia Speaks, with the aim of giving a voice to the people of Somalia and sharing a picture of how violence was impacting everyday lives. The two have since repeated this project in Mali, to share opinions about the military intervention in the north.  While Al Jazeera is a news organization, not a research institute or a government actor, it plays an important role in informing electorates who can put political pressure on governments involved in the conflict. Furthermore, this same type of technology is being used on the ground to gather information in crisis situations at the governmental and UN levels.

A call for translators in the diaspora, particularly Somali student groups, was issued online, and phones were distributed on the ground throughout Somalia so multiple users could participate. The volunteers translated the SMSs and categorized the content as either political, social, or economic. The results were color-coded and aggregated on a map.

The stated goal of the project was to give a voice to the Somali people, but the Somalis who participated had no say in how their voices were categorized or depicted on the map. The SMS poll asked an open question:

How has the Somalia conflict affected your life?

In one response example:

The Bosaso Market fire has affected me. It happened on Saturday.

The response was categorized as ‘social.’ But why didn’t the fact that violence happened in a market, an economic centre, denote ‘economic’ categorization? There was no guidance for maintaining consistency among the translators, nor any indication of how the information would be used later. It was these categories chosen by the translators, represented as bright colorful circles on the map, which were speaking to the world, not the Somalis — whose voices had been lost through a crowdsourcing application that was designed with a language barrier. The primary sources could not suggest another category that better suited the intentions of their responses, nor did they understand the role categories would play in representing and visualizing their responses to the English language audience.

An 8 December 2011 comment on the Ushahidi blog described in compelling terms how language and control over information flow impact the power balance during a conflict:

A—-, My friend received the message from you on his phone. The question says “tell us how is conflict affecting your life” and “include your name of location”. You did not tell him that his name will be told to the world. People in Somalia understand that sms is between just two people. Many people do not even understand the internet. The warlords have money and many contacts. They understand the internet. They will look at this and they will look at who is complaining. Can you protect them? I think this project is not for the people of Somalia. It is for the media like Al Jazeera and Ushahidi. You are not from here. You are not helping. It is better that you stay out.

Ushahidi director Patrick Meier, responded to the comment:

Patrick: Dear A—-, I completely share your concern and already mentioned this exact issue to Al Jazeera a few hours ago. I’m sure they’ll fix the issue as soon as they get my message. Note that the question that was sent out does *not* request people to share their names, only the name of their general location. Al Jazeera is careful to map the general location and *not* the exact location. Finally, Al Jazeera has full editorial control over this project, not Ushahidi.

As of 14 January 2012, there were still names featured on the Al Jazeera English website.

The danger is that these categories — economic, political, social — become the framework for aid donations and policy endeavors; the application frames the discussion rather than the words of the Somalis. The simplistic categories become the entry point for policy-makers and citizens alike to understand and become involved with translated material. But decisions and policies developed from the translated information are less connected to ‘real voices’ than we would like to believe.

Developing technologies so that Somalis or Libyans — or any group sharing information via translation — are themselves directing the information flow about the future of their country should be the goal, rather than perpetual simplification into the client / victim that is waiting to be given a voice.