How long is a tweet? Mapping dynamic conversation networks on Twitter using Gawk and Gephi

Twitter is now well established as the world’s second most important social media platform, after Facebook. Its 140-character updates are designed for brief messaging, and its network structures are kept relatively flat and simple: messages from users are either public and visible to all (even to unregistered visitors using the Twitter website), or private and visible only to approved ‘followers’ of the sender; there are no more complex definitions of degrees of connection (family, friends, friends of friends) as they are available in other social networks. Over time, Twitter users have developed simple, but effective mechanisms for working around these limitations: ‘#hashtags’, which enable the manual or automatic collation of all tweets containing the same #hashtag, as well allowing users to subscribe to content feeds that contain only those tweets which feature specific #hashtags; and ‘@replies’, which allow senders to direct public messages even to users whom they do not already follow. This paper documents a methodology for extracting public Twitter activity data around specific #hashtags, and for processing these data in order to analyse and visualize the @reply networks existing between participating users – both overall, as a static network, and over time, to highlight the dynamic structure of @reply conversations. Such visualizations enable us to highlight the shifting roles played by individual participants, as well as the response of the overall #hashtag community to new stimuli – such as the entry of new participants or the availability of new information. Over longer timeframes, it is also possible to identify different phases in the overall discussion, or the formation of distinct clusters of preferentially interacting participants.

Is it tweet-worthy? Privacy in a time of sharing.

Information professionals and information organisations use Twitter in a variety of ways. Typically both organisations and the individuals that work for them have separate identities on Twitter, but often individuals identify their organization through their profile or Twitter content. This paper considers the way information professionals use Twitter and their practices with regard to privacy, personal disclosure and identifying their organisational affiliations. Drawing on data from a research study involving a questionnaire and social media observation, the paper will provoke discussion about information professionals’ use of Twitter, personal and organizational identity, and the value of Twitter for professional development. In keeping with the subject matter, a curated set of social media content will be available in lieu of a formal paper.

Do monkeys tweet?

Con texto sencillo acerca de las características de algunos animales y de sus sonidos, presenta una serie de preguntas y respuestas. La última pregunta, si los búhos ululan en medio de la noche, puede ser la única vez en que la respuesta fuera afirmativa.

Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign

The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

One tweet does not a revolution make : technological determinism, media and social change

This paper discusses the problematic influence of technological determinism in popular news media coverage and analysis of the Arab Spring events of 2010-11.

The purpose is to develop insights into how and why elements of a ‘soft’ technological determinism inflect both journalistic practice and news discourse in relation to the Arab Spring. In particular it discusses how the ‘bias of convenience’ and a journalistic obsession with the ‘continuous present’ connect with this determinist inflection to create a potential distortion in the journalists’ ‘first rough draft’ of history in relation to significant and complex events such as social revolution.

Tweet reach : a research protocol for using Twitter to increase information exchange in people with communication disabilities

Objective: To (a) outline the background to research evaluating Twitter use by people with severe physical and communication disabilities participating actively in online communication forums for increasing information exchange and (b) illustrate a range of potential methods that might be applied in furthering research on the use of social media by people with developmental and acquired communication disabilities. Methods: The literature on communication disabilities, augmentative and alternative communication, and social media research informed the rationale for and design of three studies investigating the use of Twitter by people with communication disabilities. Results: To date, there is little information in the literature about how people with a range of communication disabilities might use Twitter to increase their access to information and help them to feel knowledgeable and in control of their own lives. In this paper, three studies are proposed to investigate the use of Twitter by people with communication disabilities.

DAEDALUS at PAN 2014: Guessing tweet author's gender and age

This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, develop and evaluate a simple machine learning classifier able to guess the gender and the age of a given user based on his/her texts, which could become part of the solution portfolio of the company. We were interested in finding not the best possible classifier that achieves the highest accuracy, but to find the optimum balance between performance and throughput using the most simple strategy and less dependent of external systems. Results show that our software using Naive Bayes Multinomial with a term vector model representation of the text is ranked quite well among the rest of participants in terms of accuracy.

Towards automatic tweet generation: A comparative study from the text summarization perspective in the journalism genre

In recent years, Twitter has become one of the most important microblogging services of the Web 2.0. Among the possible uses it allows, it can be employed for communicating and broadcasting information in real time. The goal of this research is to analyze the task of automatic tweet generation from a text summarization perspective in the context of the journalism genre. To achieve this, different state-of-the-art summarizers are selected and employed for producing multi-lingual tweets in two languages (English and Spanish). A wide experimental framework is proposed, comprising the creation of a new corpus, the generation of the automatic tweets, and their assessment through a quantitative and a qualitative evaluation, where informativeness, indicativeness and interest are key criteria that should be ensured in the proposed context. From the results obtained, it was observed that although the original tweets were considered as model tweets with respect to their informativeness, they were not among the most interesting ones from a human viewpoint. Therefore, relying only on these tweets may not be the ideal way to communicate news through Twitter, especially if a more personalized and catchy way of reporting news wants to be performed. In contrast, we showed that recent text summarization techniques may be more appropriate, reflecting a balance between indicativeness and interest, even if their content was different from the tweets delivered by the news providers.

Two studies on Twitter networks and tweet content in relation to Amyotrophic Lateral Sclerosis (ALS): conversation, information, and ‘Diary of a Daily Life’

To date, there is no research examining how adults with Amyotrophic Lateral Sclerosis (ALS) or Motor Neurone Disease (MND) and severe communication disability use Twitter, nor the use of Twitter in relation to ALS/MND beyond its use for fundraising and raising awareness. In this paper we (a) outline a rationale for the use of Twitter as a method of communication and information exchange for adults with ALS/MND, (b) detail multiple qualitative and quantitative methods used to analyse Twitter networks and tweet content in the our studies, and (c) present the results of two studies designed to provide insights on the use of Twitter by an adult with ALS/MND and by #ALS and #MND hashtag communities in Twitter. We will also discuss findings across the studies, implications for health service providers in Twitter, and directions for future Twitter research in relation to ALS/MND.

Microblogging as a literacy practice for educational communities

Microblogging is an emergent adolescent and adult literacy practice that has become popularized through platforms such as Twitter, Plurk and Jaiku, in the rise of Web 2.0 – “the social web”. Yet the potentials of microblogging for literacy learning in educational contexts is currently underexplored in the research and literature. This article draws on new research with 150 adolescent and adult participants in school and university contexts, which was made possible through cross-disciplinary collaboration between specialists English and Information and Communication Technologies (ICT) educators. Strategies are provided for teachers to establish their own microblogging networks, with suggested activities to enhance the literacy learning of adolescents in educational contexts.

New methodologies for researching news discussion on Twitter

Twitter has become a major instrument for the rapid dissemination and subsequent debate of news stories. It has been instrumental both in drawing attention to events as they unfolded (such as the emergency landing of a plane in New York’s Hudson River in 2009) and in facilitating a sustained discussion of major stories over timeframes measured in weeks and months (including the continuing saga around Wikileaks and Julian Assange), sometimes still keeping stories alive even if mainstream media attention has moved on elsewhere. More comprehensive methodologies for research into news discussion on Twitter – beyond anecdotal or case study approaches – are only now beginning to emerge. This paper presents a large-scale quantitative approach to studying public communication in the Australian Twittersphere, developed as part of a three-year ARC Discovery project that also examines blogs and other social media spaces. The paper will both outline the innovative research tools developed for this work, and present outcomes from an application of these methodologies to recent and present news themes. Our methodology enables us to identify major themes in Twitter’s discussion of these events, trace their development and decline over time, and map the dynamics of the discussion networks formed ad hoc around specific themes (in part with the help of Twitter #hashtags: brief identifiers which mark a tweet as taking part in an established discussion). It is also able to identify links to major news stories and other online resources, and to track their dissemination across the wider Twittersphere.

Researching news discussion on Twitter : New methodologies

Twitter has become a major instrument for the rapid dissemination and subsequent debate of news stories, and comprehensive methodologies for systematic research into news discussion on Twitter are beginning to emerge. This paper outlines innovative approaches for large-scale quantitative research into how Twitter is used to discuss and cover the news, focusing especially on #hashtags: brief identifiers which mark a tweet as taking part in an established discussion.