What's up with Twitter, in fewer than 10,000 characters

The internet erupted in outrage last week at reports that Twitter is poised to increase the limit for tweets from 140 to 10,000 characters. The first rumours of such a move emerged in the tech news website Re/code back in September then again last week. The response on Twitter was immediate and, for the most part, somewhere between incensed and bemused, with many thousands of tweets posted with hashtags such as #10kTwitter, #Twitter10k, #10000gate, #140twitter, #beyond140 and #longtweets...

On hashtaggery and portmanteaugraphy: Memetic wordplay as social media practice

I wouldn’t necessarily consider myself a meme scholar outright; rather, the memes within my research have emerged from studying everyday practices and cultures of social media, within political and topical discussions, as well as popular culture and fandom contexts. This piece is an extension of ideas that have come out of my recent work around the “irreverent internet” (in the first and last of the blatant plugs, see this [sorry, paywall] and this). I’ve used this term as a descriptor for how play and silliness are popular strategies for the coverage and presentation of the topical and the mundane online. Here, I am especially focusing on playful and irreverent engagement with issues, events, and breaking news, where irony, sarcasm, parody, satire, snark, and more, are important framing devices on social media. While my work (and this post) generally falls on the side of “nice” irreverence, these approaches are also applicable for meaner, vindictive, hateful, offensive, and vitriolic comments. These include meme communities dealing in racist attitudes and content or various hashtags and related comments which promote racist, far-right views and/or denote contexts rife with abuse and harassment — and not just the Gamergate example. This is not positioning trolling as a single practice or intent, either— see Whitney Phillips’ work...

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.

The visual representation of the “indignados”. A visual analysis about the characterization of the participants of the 15-M movement.

The aim of this work is to show the type of media coverage done by the newspapers La Razón, El País and Público about the 15-M social movement during the time that the camping at Sol took place. Specifically, in terms of how the characterization of the “indignados” (outraged) got made. Based on our previous descriptive observations, we approached a visual analysis of the photographs published on the paper editions of those mainstream media from May 15-June 12 of the 2011. we started from a total sample of 379 items, developing:1) A content analysis of La Razón, El País, and Público; the most frequents words of each media, articles classifications from the reviews found on them (expositive, positive-evaluation, negative-evaluation).2) An analysis of the 408 images obtained from the total sample, which establishes a clear evolution of the “indignados” profile and how differently each media took the movement as such. That’s, when they stop naming them “indignados”, and recognize its nature as social movement by calling it: “Movimiento 15-M"...

Détection d'évènements à partir de Twitter

Nous proposons dans cette thèse un système permettant de déterminer, à partir des données envoyées sur les microblogs, les évènements qui stimulent l’intérêt des utilisateurs durant une période donnée et les dates saillantes de chaque évènement. Étant donné son taux d’utilisation élevé et l’accessibilité de ses données, nous avons utilisé la plateforme Twitter comme source de nos données. Nous traitons dans ce travail les tweets portant sur la Tunisie dont la plupart sont écrits par des tunisiens. La première tâche de notre système consistait à extraire automatiquement les tweets d’une façon continue durant 67 jours (de 8 février au 15 avril 2012). Nous avons supposé qu’un évènement est représenté par plusieurs termes dont la fréquence augmente brusquement à un ou plusieurs moments durant la période analysée. Le manque des ressources nécessaires pour déterminer les termes (notamment les hashtags) portant sur un même sujet, nous a obligé à proposer des méthodes permettant de regrouper les termes similaires. Pour ce faire, nous avons eu recours à des méthodes phonétiques que nous avons adaptées au mode d’écriture utilisée par les tunisiens, ainsi que des méthodes statistiques. Pour déterminer la validité de nos méthodes, nous avons demandé à des experts, des locuteurs natifs du dialecte tunisien, d’évaluer les résultats retournés par nos méthodes. Ces groupes ont été utilisés pour déterminer le sujet de chaque tweet et/ou étendre les tweets par de nouveaux termes. Enfin, pour sélectionner l'ensemble des évènements (EV), nous nous sommes basés sur trois critères : fréquence, variation et TF-IDF. Les résultats que nous avons obtenus ont montré la robustesse de notre système.

TRCM: a methodology for temporal analysis of evolving concepts in Twitter

The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper.

Rule Type Identification using TRCM for trend analysis in Twitter

This paper considers the use of Association Rule Mining (ARM) and our proposed Transaction based Rule Change Mining (TRCM) to identify the rule types present in tweet’s hashtags over a specific consecutive period of time and their linkage to real life occurrences. Our novel algorithm was termed TRCM-RTI in reference to Rule Type Identification. We created Time Frame Windows (TFWs) to detect evolvement statuses and calculate the lifespan of hashtags in online tweets. We link RTI to real life events by monitoring and recording rule evolvement patterns in TFWs on the Twitter network.

Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis

Notwithstanding recent work which has demonstrated the potential of using Twitter messages for content-specific data mining and analysis, the depth of such analysis is inherently limited by the scarcity of data imposed by the 140 character tweet limit. In this paper we describe a novel approach for targeted knowledge exploration which uses tweet content analysis as a preliminary step. This step is used to bootstrap more sophisticated data collection from directly related but much richer content sources. In particular we demonstrate that valuable information can be collected by following URLs included in tweets. We automatically extract content from the corresponding web pages and treating each web page as a document linked to the original tweet show how a temporal topic model based on a hierarchical Dirichlet process can be used to track the evolution of a complex topic structure of a Twitter community. Using autism-related tweets we demonstrate that our method is capable of capturing a much more meaningful picture of information exchange than user-chosen hashtags.

Ataque na França estimula debate no mundo sobre liberdade de expressão

O ataque ao semanário francês Charlie Hebdo, em Paris, no início de janeiro, polarizou as redes sociais através das manifestações Je suis Charlie e Je ne suis pas Charlie Para entender os discursos e razões de cada grupo, a Diretoria de Análise de Políticas Públicas monitorou as redes sociais entre os dias 7 e 19 de janeiro. As nuvens de palavras abaixo representam as respectivas hashtags #jesuischarlie e #jenesuispascharlie, e através delas é possível observar os diferentes discursos a partir dos termos e palavras relacionadas a cada expressão que foi usada durante esses dias. No total, foram mais de 3 milhões de tuítes coletados, nos idiomas inglês, francês, português e espanhol.

Oscar 'político' repercute nas redes sociais

Neste domingo, na noite de 22 de fevereiro, ocorreu no Dolby Theatre, em Los Angeles, a 87ª cerimônia de entrega do Oscar, que foi marcada por discursos politizados e de cunho reivindicatório – e que, inclusive, roubaram a cena nas redes sociais dos filmes e astros que ganharam prêmios. A quantidade de menções no Twitter ao Oscar, com as respectivas hashtags, dá a justa medida da relevância do evento: em 24 horas, foram 11,4 milhões de postagens no mundo inteiro, segundo levantamento da FGV/DAPP.

Greve dos caminhoneiros tem forte repercussão nas redes sociais

A greve de caminhoneiros, que já atinge 12 estados, começa a impactar o abastecimento nas principais cidades do país, alcançando forte repercussão nas redes sociais. Os protestos, iniciados no fim de semana, provocam também congestionamentos nas rodovias e prejuízos à exportação. As reivindicações dos caminhoneiros, no entanto, encontram respaldo de parte dos usuários das redes, sobretudo o aumento nos preços dos combustíveis. As hashtags mais usadas são #apoiocaminhoneiros e #caminhoneiros.

Aprovação da redução da maioridade penal em Comissão da Câmara divide opiniões nas redes

Jornal da Globo News apresentado por Leilane Neubarth

Hummingbird: Privacy at the time of Twitter

In the last several years, micro-blogging Online Social Networks (OSNs), such as Twitter, have taken the world by storm, now boasting over 100 million subscribers. As an unparalleled stage for an enormous audience, they offer fast and reliable centralized diffusion of pithy tweets to great multitudes of information-hungry and always-connected followers. At the same time, this information gathering and dissemination paradigm prompts some important privacy concerns about relationships between tweeters, followers and interests of the latter. In this paper, we assess privacy in today?s Twitter-like OSNs and describe an architecture and a trial implementation of a privacy-preserving service called Hummingbird. It is essentially a variant of Twitter that protects tweet contents, hashtags and follower interests from the (potentially) prying eyes of the centralized server. We argue that, although inherently limited by Twitter?s mission of scalable information-sharing, this degree of privacy is valuable. We demonstrate, via a working prototype, that Hummingbird?s additional costs are tolerably low. We also sketch out some viable enhancements that might offer better privacy in the long term.

#DressCodePM & Re-Framing The Niqab: News Sources, Hashtag Activism, and Media Representation

This thesis originates from my interest in exploring how minorities are using social media to talk back to mainstream media. This study examines whether hashtags that trend on Twitter may impact how news stories related to minorities are covered in Canadian media. The Canadian Prime Minister Stephen Harper stated the niqab was “rooted in a culture that is anti-women” on 10 March 2015. The next day #DressCodePM trended in response to the PM’s niqab remarks. Using network gatekeeping theory, this study examines the types of sources quoted in the media stories published on 10 and 11 March 2015. The study’s goal is to explore whether using tweet quotes leads to the representation of a more diverse range of news sources. The study compares the types of sources quoted in stories that covered Harper’s comments without mentioning #DressCodePM versus stories that mention #DressCodePM. This study also uses Tuen A. van Dijk’s methodology of asking “who is speaking, how often and how prominently?” in order to examine whose voices have been privileged and whose voices have been marginalized in covering the niqab in Canadian media from the 1970s and until the days following the PM’s remarks. Network gatekeeping theory is applied in this study to assess whether the gated gained more power after #DressCodePM trended. The case study’s findings indicates that Caucasian male politicians were predominantly used as news sources in covering stories related to the niqab for the past 38 years in the Globe and Mail. The sourcing pattern of favouring politicians continued in Canadian print and online media on 10 March 2015 following Harper’s niqab comments. However, ordinary Canadian women, including Muslim women, were used more often than politicians as news sources in the stories about #DressCodePM that were published on 11 March 2015. The gated media users were able to gain power and attract Canadian Media’s attention by widely spreading #DressCodePM. This study draws attention to the lack of diversity of sources used in Canadian political news stories, yet this study also shows it is possible for the gated media users to amplify their voices through hashtag activism.

#DressCodePM & Re-Framing The Niqab: News Sources, Hashtag Activism, and Media Representation

This thesis originates from my interest in exploring how minorities are using social media to talk back to mainstream media. This study examines whether hashtags that trend on Twitter may impact how news stories related to minorities are covered in Canadian media. The Canadian Prime Minister Stephen Harper stated the niqab was “rooted in a culture that is anti-women” on 10 March 2015. The next day #DressCodePM trended in response to the PM’s niqab remarks. Using network gatekeeping theory, this study examines the types of sources quoted in the media stories published on 10 and 11 March 2015. The study’s goal is to explore whether using tweet quotes leads to the representation of a more diverse range of news sources. The study compares the types of sources quoted in stories that covered Harper’s comments without mentioning #DressCodePM versus stories that mention #DressCodePM. This study also uses Tuen A. van Dijk’s methodology of asking “who is speaking, how often and how prominently?” in order to examine whose voices have been privileged and whose voices have been marginalized in covering the niqab in Canadian media from the 1970s and until the days following the PM’s remarks. Network gatekeeping theory is applied in this study to assess whether the gated gained more power after #DressCodePM trended. The case study’s findings indicates that Caucasian male politicians were predominantly used as news sources in covering stories related to the niqab for the past 38 years in the Globe and Mail. The sourcing pattern of favouring politicians continued in Canadian print and online media on 10 March 2015 following Harper’s niqab comments. However, ordinary Canadian women, including Muslim women, were used more often than politicians as news sources in the stories about #DressCodePM that were published on 11 March 2015. The gated media users were able to gain power and attract Canadian Media’s attention by widely spreading #DressCodePM. This study draws attention to the lack of diversity of sources used in Canadian political news stories, yet this study also shows it is possible for the gated media users to amplify their voices through hashtag activism.