Subscribe: Snurb's blog
Added By: Feedage Forager Feedage Grade B rated
Language: English
content  data  facebook  fake  media  news  number  practices  reply  selfies  social media  social  time  trump  tweets 
Rate this Feed
Rate this feedRate this feedRate this feedRate this feedRate this feed
Rate this feed 1 starRate this feed 2 starRate this feed 3 starRate this feed 4 starRate this feed 5 star

Comments (0)

Feed Details and Statistics Feed Statistics
Preview: Snurb's blog

Snurb's blog

Research, rants, and random thoughts by Axel Bruns.


Donald Trump's Campaign and the Hybrid Media System

Thu, 19 Oct 2017 16:42:56 +0000

PoliticsElectionsJournalism'Big Data'Social MediaTwitterAoIR 2017The first keynote at AoIR 2017 is by Andrew Chadwick, who explores what the 2016 U.S. presidential campaign means for our understanding of the hybrid media system. Political communication is in the middle of a chaotic transitional period, due in good part to the disruptions brought by newer, digital media; some older media have also been renewed by integrating the logics of newer media. This then represents a systemic perspective that examines forces while they are in flow.The hybrid media system is built on the interactions of older and newer media logics in the reflexively connected field of media and politics. Actors in this field tap and steer information flows in ways that suit their goals, enable or disable the agency of others, across various older and newer media settings. 'Hybrid' here shifts our conceptualisation from 'either/or' to 'not only, but also'; it foregrounds complexity, interdependence and transition. We pay more attention to boundaries, flux, and liminal spaces, where practices intermeshing and co-evolve.This also means studying the power relations between social actors, and understanding the systems that exist horizontally and vertically between them and that from time to time undergo long and chaotic periods of change. Within systems, even the most powerful actors often need to cooperate with those who have less power, and power is relational and situationally dependent; in a digital environment, these institutions and their relationships are now comparatively loose, ad hoc, and spontaneous, and highly adaptable to current contexts: they can be understood as assemblages – built around permeable boundaries between different entities engaged in particular endeavours.Power and systems are also dependent upon time; there is a need for a mastery of technical rhythms, that is, for timeliness, especially in increasingly real-time environments. Temporal power is now enabled or constrained in different ways by different media, and it is enacted and re-enacted differently.Which brings us to the Presidency of Donald J. Trump. His White House has been in chaos since day one; many early advisers have already been fired or have resigned. Press Secretary Sean Spicer started his job with a need to deal with Trump's blatant lie about the size of his inauguration crowd, for example; rapid work by a Reuters news photographer, his editorial office, and other media made the comparison between Trump's and Obama's crowds echo around the world almost before Trump was finished speaking.One of the largest demonstrations during the early days of the Trump Presidency, the Women's March, began from a social media post by a Hawai'ian activist, which over night attracted support from a diverse coalition of major activist organisations; it also featured many participants wearing 'pussyhats', responding to candidate Trump's comments about his sexual harassment activities. The Women's March protests occurred on the day after the inauguration, as Trump was giving a public speech at CIA headquarters, and well eclipsed the size of Trump's inauguration crowds.So, one of Spicer's first acts in office was to defend Trump's lies about the inauguration crowd; but he attempted to follow a pre-digital media approach that presented scripted statements: the arguments he presented were clearly untrue, and quickly debunked by a coalition of mainstream and social media actors who presented copious evidence to the contrary. Such articles, posts, and tweets was further embedded in high-traffic sites including Buzzfeed.In turn, The New York Times collated much of this material as well as some additional original research in its fact-checking column to demolish every single claim made by Trump and Spicer. Various historical documents and other source data were presented to support the article's conclusions. Trump spokesperson KellyAnne Conway ended up defining Spicer's and Trump's statements as "alternative facts", much to the amusement of professional journalists.The debun[...]

Selfie Practices on Instagram during Major Events

Thu, 19 Oct 2017 14:13:36 +0000

The final paper in this AoIR 2017 session is by Gemma San Corneliu and Antoni Roig, whose focus is on the study of selfies as performed personal narratives, in a broader context of narrative texts. How may such selfies be understood through an alternative genealogy that conceptualised selfies as small narratives?

Narratives are generally very important in social media; overall, they create identity at all levels of human life. New narrative models may be emerging from the analysis of selfies, and this project pursued the identification of these narratives through a series of case studies. The researchers focussed both on users and hashtags on Instagram.

The project scraped the Instagram API for 24 hours during the Primavera Sound 2016 festival, using the festival's hashtag; the researchers also conducted some ethnographic fieldwork and participant observation during this time. Selfies during this time represented some 15% of the photos posted, and the tag #selfie was generally not used in these posts. Other tags related to the festival brand and the bands performing at the festival. Participants distinguished between the 'legitimate selfie' (taken to document attendance and fandom) and the 'posing selfie' (seen as more artificial and inauthentic). Most pictures were posted during the performance of headliner Suede, but not all of these related to that performance.

A second case, using identical methodology, focussed on the BCN Games World exhibition. Here, selfies represented some 17% of all posts, but a high volume (33%) of portraits were also present in the data: more than half of all images depicted people at the event. Many of the selfies were taken with selfie sticks. Most hashtags again focussed on the exhibition's brand as well as on the exhibitors, while participants were reluctant to talk about social media uses that were not related to professional practices.

One of the challenges is now to craft the narrative emerging from the research itself, also in terms of appropriate data visualisation. Already, there is an indication that selfies represent only one minority image practice at these events; they remain significant, but portraying others is also important. The #selfie tag itself appears to be falling out of favour, and it is therefore importantly to regard selfies in the context of all the other image types being uploaded from the same events. Selfies may be concentrated around specific aspects of these events, with other image types being used a other times or in other locations.


Reply Trees in the Australian Twittersphere

Thu, 19 Oct 2017 14:13:13 +0000

The next speaker in this AoIR 2017 is my DMRC colleague Brenda Moon, whose focus is on reply chains on Twitter. There are a number of ways in which replies are chained together, and in fact the term 'reply tree' may be preferable to 'reply chains': there may be many replies to the same original tweet only, or a long dyadic interaction over a series of tweets, or various permutations between these two extremes.

Brenda's work uses the TrISMA dataset of all tweets sent by Australian accounts over several years; this may miss tweets in a reply tree if those tweets are not part of the Australian dataset (e.g. because they were not sent by Australian accounts). Except for this, however, reply trees can be constructed by using the 'in_reply_to' field in the tweet metadata, and the entire dataset of more than 2 billion tweets can be processed (with some difficulties) to assign each @reply to a unique reply tree ID.

Some 20% of all tweets belong to a reply tree, and some 15% of these reply to tweets by other Australian accounts. Across the entire dataset, the vast majority of these trees are very short (five steps or less). The trees with with considerable user involvement tend to have relatively few steps (they represent star networks), while trees with few participants can operate over longer instances. The largest tree consists largely of single-level responses to a teen idol promoting his latest album. The longest tree consists of some 230 responses between only two accounts, over the course of some two months.

The focus on Australian accounts' tweets only may slightly alter these patterns, of course, and patterns in other nations may also differ. In Australia, at any rate, there does not seem to be much variation in these patterns over the years, even in spite of Twitter's continued tweaks to reply functionality. There's also a need to explore whether the specific shapes of reply trees are related in any way to the themes or tone of discussions on Twitter.


Testing the Validity of Twitter API Data

Thu, 19 Oct 2017 14:12:29 +0000

The next speaker in this AoIR 2017 session is Rebekah Tromble, whose focus is on the impact of digital data collection methods on scientific inference. Collecting data from social media APIs, how can we know whether we have 'good', valid data?

Twitter, for instance, provides a range of open APIs as well as commercial-quality data access via its subsidiary GNIP; the open streaming API offers up to 1% of the total global Twitter throughput, but potentially offers 100% of the tweets matching specific keywords or hashtags; and the open search API offers access to historical tweets, but also with significant limitations.

Rebekah's project tried a number of different data captures across these three data sources, using the #jointsession hashtag for President Trump's first address to Congress, the #ahca hashtag about the House of Representatives failed vote on healthcare, and the #fomc hashtag for the Federal Open Market Committee; additionally, it also captured all tweets mentioning @realdonaldtrump on Trump's inauguration day.

For some of these events, the streaming API was substantially rate-limited (at around 65% of all tweets). Search also resulted in only a limited (but larger) subset of tweets for these events. The project then tested the variables that potentially influenced which tweets from the total set of matching tweets (as captured via GNIP) were delivered via the rate-limited open APIs – do user properties or tweet properties influence which tweets are selected?

Search appears to be influenced by a range of variables, while streaming shows a more limited set of factors. Overall, when rate limits do not apply, the streaming API approximates the full tweet population. But for short-term, rate-limited data, the API may well introduce important biases in the dataset collected.

Social Media Bullshit on the Facebook 'Peace' Page

Thu, 19 Oct 2017 14:07:52 +0000

The next session at AoIR 2017 starts with this year's AoIR Nancy Baym Book Award winner Nicholas John, whose focus here is on unfriending practices in the context of specific political events. There is limited information about unfriending as the platforms themselves do not provide a great deal of information about such practice.

However, offers data on Facebook ties across national divides (e.g. between Pakistan and India, or Palestine and Israel), and such data may potentially be valuable in this context. Unfortunately, though, the data provided by Facebook and the Stanford Peace Innovation Lab on this page is highly dubious, however.

The page operated in 2013, was mothballed for some time, and relaunched in February 2015; there was a substantial decline in numbers of friendships between Palestinian and Israeli users from June 2013 to February 2015; between November 2015 and early 2016 the number increased again by a factor of ten.

This is necessarily suspicious, even taking into account potential increases in the overall number of accounts. By Facebook's numbers, people would need to pick up some 8.5 friends across national divides per week (month?) – this is exceptionally unlikely. Independent surveys of Facebook friending behaviour also do not bear out these patterns.

Friending patterns also don't seem to follow other Facebook usage patterns in Israel, for instance: usage declines substantially around major religious holidays, for instance, yet friending appeared to continue. Nic queried Facebook about these discrepancies, and interestingly around the same the page stopped updating; it remains online, however, and continues to claim that the (now static) numbers represent new friendships over the past week.

Perhaps, then, the 'peace' page is an excellent example of social media bullshit. Perhaps the creators of the page are not concerned about the validity of these numbers at all; perhaps the numbers reported here since 2016 were massaged to 'appear' more impressive, in order to create the impression that Facebook contributes to world peace by connecting more people on a more personal basis.

The numbers claim to be real-time, high-volume, and accurate. They are created by Facebook, which should know the real numbers, and they draw on the semiotics of 'big data'. This raises real questions about how much we should trust Facebook in anything, and moves us from social media epistemology to social media agnotology: it highlights our continuing ignorance about some crucial, central aspects of social media.

The Thin Line between Legitimate and Illegitimate Social Media Marketing Practices

Thu, 19 Oct 2017 12:01:40 +0000

The next speaker in this AoIR 2017 session is Thomas Beauvisage, who begins by highlighting the algorithmic ordering of content in social media. This is also a form of reputational capital, and has led to the development of a rogue industry providing 'fake' followers, likes, and other quantifiable measures of apparent user interest.

This is related to a range of standard attentional techniques and encoded in standardised, industry-recognised metrics. Some of these metrics are generated through social bots and other forms of online automation, and represent a form of sometimes playful numeric manipulation. But what is this 'black' market? Who are the companies and individual behind it, and what is their position in the attention economy?

These illegitimate practices are strongly linked with legitimate practices in the social media marketing industry; some of the businesses certainly consider themselves as ordinary, legitimate businesses. Thomas and his colleagues conducted interviews with practitioners in both legitimate and illegitimate businesses in France, in both 2013 and 2016.

Social media marketing was very attractive to marketers early on, as it promised a more direct relationship with customers, and enlisted customers themselves in the viral sharing of content. The early industry consisted of a range of emerging, experimental agencies that presented untested, raw metrics as evidence of their success. However, such viral distribution has remained elusive other than in a small number of unusual cases; parts of the industry were also found to engage in dubious practices such as the creation of 'fake followers' and the artificial pump-priming of viral campaigns.

Today, the industry involves spontaneous community management elements as well as routinised online advertising practices. Fake metrics services, too, have standardised their products, with typical quantities of likes or followers (500 / 1000 / 10,000 / ...) now readily available from a range of companies, which also aids price comparison between different services. As part of this, companies also sell access to networks of real users who follow popular thematic pages, country targetting, and manual promotion work (often by low-paid clickworkers in countries like Bangladesh or India).

These companies largely see their activities as illegitimate, but not illegal; some of the larger operation seek legitimacy. Their customers, too, see them as a necessary evil, given the attention economy within which they operate. Platforms continue to fight back against such cheating practices, but there is a substantial amount of automation in this environment, and some legitimate bots and companies are also operating in this space. There is therefore now also a continuity between legitimate and illegitimate practices, on historical, technical, entrepreneurial, and customer levels. The gaming of digital metrics continues, in marketing (through SEO, linking, ratings, etc.) as much as in politics (through 'fake news' and other practices).


Patterns in Media References in the Dutch Twittersphere

Thu, 19 Oct 2017 12:01:30 +0000

The second paper in this AoIR 2017 session is by Daniela van Geenen and Mirko Schäfer, whose focus is on 'fake news' on Twitter. They began by tracking activities in the Dutch Twittersphere, and identified a number of communities within this userbase; within these communities, news and other information are being shared, and a process of social filtering takes place.

Within a two-week sample of Dutch tweets, the project identified the references to traditional and alternative media sources; the former represented established media including broadcasters, newspapers, and similar outlets, while the latter were often online-only, topic-focussed sites that were not necessarily run by professional journalists. Traditional media were referred to in some 211,000 tweets, while 44,000 tweets referred to alternative media.

Out of this dataset, the project also identified a subset of highly active retweet networks, including especially a right-wing cluster that accounted for some 50% of all alternative media references. Other clusters covered left-wing politics, environmentalism, sports, vlogging, and other topics. A smaller left-wing clusters also shared a substantial amount of alternative media.

Tabloid content was shared especially in the right-wing cluster as well, with some attention also in the left-wing cluster (though the framing of these links may well differ across these groups). An analysis of framing approaches in a sample of these tweets showed that the framing of alternative media references is largely affirmative; traditional media references are similarly mainly affirmed, but with a greater percentage of negotiated and oppositional readings, and some tweets also concern the medium itself rather than the content published there. Tabloids are more frequently referenced than quality news sources; here, too, it is often the medium than the specific content that is endorsed.

There is a need to further extend the analysis from this sample to a larger subset of the dataset. Additionally, the styles of framing might intersect with the practices common on the platform. There is a bricolage of re-encoding of content: the dissemination is socially rather than algorithmically driven. This complicates the encoding/decoding model and introduces a number of additional levels of encoding. Finally, the notion of 'filter bubbles' and 'echo chambers' needs to be challenged: network visualisations in their identification of clusters generally promote a focus on such supposed structures, but this may obscure a more complex reality.


Governance and Regulation on Social Media Platforms

Thu, 19 Oct 2017 11:44:26 +0000

It is already the middle of the first day of AoIR 2017, and I'm finally getting to see a panel, on 'fake news', which starts with Christian Katzenbach and Kirsten Gollatz. They start by noting the increasing discussion about platform governance initiatives designed to limit the circulation of 'fake news', however the term is defined; this also builds on considerable amounts of research into the politics of platforms.

But there is a conceptual gap (where and what is the governance in platforms?) and an empirical gap, with a lack of a long-term view on platform governance. Governance on platforms might mean law, terms of service, algorithmic or human governance processes, etc.; there is a turn also to practice theory and discourse theory that doesn't simply take a legalistic, regulatory approach.

The central question here is, or should be, the ordering and coordination of digital communication. For this, legal and regulatory interventions might be mobilised, but other governance approaches may also be relevant. Governance and regulation need to be distinguished: governance is a long-term, meandering process, while regulation represents intentions interventions into these processes and incorporates a number of different modes of ordering that interact with each other.

How might these theoretical ideas be put into practice? The empirical part of this study examines Facebook as a platform, and combines text and content analysis, document and discourse analysis, to track the factual rule changes, as well as the public perception of these rules, on this platform over time. Facebook's standards for what is inappropriate content have varied over time; there were vague statements about inappropriate content at first, which have become increasingly detailed and complex over time (if not necessarily much clearer).

Policy on nudity has changed from a general restriction on nudity to a more detailed list of specific prohibited content, for example, also alongside a growing list of exceptions (e.g. pictures of breastfeeding or mastectomy scars, or images of paintings or sculptures). Hate speech has been defined in increasingly detailed statements, too, and this also reflects the changing issues being addressed in hate speech acts on Facebook (with recent issues especially around hate speech against refugees and women). Policies on 'fake' content are still evolving, too; early concerns focussed on fake profiles and the impersonation of public figures, while much more attention is now being paid to the sharing of 'fake news' and other misleading material on current events.

There is, then, an ongoing battle over what content is allowed on this platform; the standards continue to change, and discourses about them show enable an observation of policy changes. Critical moments serve as moments of contestation and justification, yet the communities involved in these discussions differ substantially between the different areas of content policy explored here.


The Problem with Objectivity in Journalism

Fri, 15 Sep 2017 15:36:17 +0000

Gatewatching and Citizen JournalismJournalismIndustrial JournalismFuture of Journalism 2017The final keynote speaker at Future of Journalism 2017 is Linda Steiner, who begins by introducing us to feminist standpoint epistemology: bodies of knowledge are socially situated and embodied, and this both limits and enables what one can know. From this perspective, it is clear that there is a thin procedural view of objectivity at the basis of journalism – and this is a problem. This is simultaneously also a reason that Donald Trump and other critics of the mainstream media are able to attack the press as 'fake news' when it does not live up to a narrow standard of objectivity, and a reason that journalists themselves will choose to cover more straightforward stories rather than topics that would challenge their ability to remain objective.There is therefore now also a moral panic over news consumption, as many audiences are turning away from the sometimes anaemic news coverage of the mainstream media and towards more engaging, partisan, energetic, and entertaining forms of news coverage and discussion. Indeed, these audiences are increasingly also admitting and celebrating their preferences for 'soft' and entertaining over 'hard' and dry news. This means that the paradigm of objectivity is now beyond repair, and needs replacement, Linda suggests.Feminist standpoint epistemology, then, is a knowledge project that challenges ethnocentric, sexist claims to value-neutrality in science; it aims to reshape science to be less false; and it seeks to be more democratic and more engaged. These aims can also be applied to journalism: objectivity serves dominant groups; conventional views of objectivity are too weak to identify the interests and values that shape agendas, contents, and results of inquiry; it seeks to improve the process of fact-finding, not of selecting issues and topics in the first place; and it focusses on the point of verification rather than the process of discovery of facts.Instead, there is a need for strong method, strong reflexivity, strong objectivity, and strong ethics to combine in journalism in order to produce strong information. The approach resists the suggestion that we all have our equally valid interpretations of the facts; instead, it allows for historical and cultural relativism, meaning that our personal backgrounds influence how we evaluate information, but not for epistemological and judgmental relativism. Indeed, outsiders to social order are more likely to generate critical questions about received beliefs, due to their own bifurcated consciousness, even if they are themselves also grounded in their own historical specificities.Strong method, then, means transparency, accountability, comprehensiveness, interrogated with reflexivity and and awareness of subjectivity. Inquiry starts from the lived experience of people who are usually excluded from knowledge production; this generates more critical questions and can generate greater insights into the object of study. The aim is for the provisionally least false, discarding false beliefs when counter-evidence or new conceptual frameworks offer better insights.In this, the work of alternative media, when they represent a diverse range of journalists, adds crucial diversity by drawing on a variety of non-privileged sources; they develop transparency and self-conscious politics; they share control over their stories with the subjects and sources of those stories; they experiment with accountability; and they commit to group self-reflexivity. In this, they clearly stand apart from conventional news media. Given the perilous state of mainstream news, we have little to lose from further embracing this revolutionary model.[...]

Does Using Social Media for News Change Attitudes to the EU?

Fri, 15 Sep 2017 14:00:14 +0000

The final speaker in this Future of Journalism 2017 session is An Nguyen, who begins by focussing on the role of major tech companies in influencing information exposure for their users, which has given rise to concepts like 'echo chambers' and 'filter bubbles'. Various studies have now started to explore the presence of such patterns, building on a variety of data and focussing on a range of contexts, communities, and cases – with highly variable outcomes.

The present study uses the Eurobarometer 86.2 survey, to explore whether in the turmoil of 2016 EU publics changed their views on social media as sources of political news. To what extent do they rely on social media, and under what circumstances; how does this impact on their level political knowledge? The survey covers some 28,000 participants from 28 EU member states, during the first fortnight of November 2016.

First, in spite of events like Brexit and the Trump election, the survey respondents' attitudes towards social media as sources of political news have improved substantially. Reliance on social media for political news is mainly related to age, with younger users more likely to rely on social media; such users are also more likely to trust what they see on such social media platforms. There is no practical effect on political attitudes, however: social media users are no more likely to see the EU in a positive or negative light across a number of evaluative dimensions, compared to non-users.

This is likely to mean that people rely on social media for news not because of pre-existing attitudes towards the EU or towards the mainstream news media, but instead mainly for other demographic reasons, including especially their age. This also means that 'echo chamber' and 'filter bubbles' must be revisited, and moral panics about social media should be questioned.