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The purpose of this paper is to describe and analyse relationships and communication between Twitter actors in Swedish political conversations. More specifically, the paper aims to identify the most prominent actors, among these actors identify the sub-groups of actors with similar political affiliations, and describe and analyse the relationships and communication between these sub-groups.

Data were collected during four weeks in September 2012, using Twitter API. The material included 77,436 tweets from 10,294 Twitter actors containing the hashtag #svpol. In total, 916 prominent actors were identified and categorised according to the main political blocks, using information from their profiles. Social network analysis was utilised to map the relationships and the communication between these actors.

There was a marked dominance of the three main political blocks among the 916 most prominent actors: left block, centre-right block, and right-wing block. The results from the social network analysis suggest that while polarisation exists in both followership and re-tweet networks, actors follow and re-tweet actors from other groups. The mention network did not show any signs of polarisation. The blocks differed from each other with the right-wingers being tighter and far more active, but also more distant from the others in the followership network.

While a few papers have studied political polarisation on Twitter, this is the first to study the phenomenon using followership data, mention data, and re-tweet data.

Social media connect individuals in different geographical location and allow people of different political and cultural backgrounds to discuss and participate in events that occur in distant corners of the globe. But, this does not suggest that social media promote homogeneous globalization. Rather, the local and its interactions with the global or regional views remain a powerful force in the realm of social media. The purpose of this paper is to take on the local/global factors in the social media service Twitter and analyzed the keyword-captured Chinese language tweets relating to the 2012 presidential election in Taiwan.

Language code usage was used to sort out the community origins of Chinese language tweets relating to the election, given that distinct types and codes of Chinese characters are used within each political border. Community-specific patterns of communication were identified by cross-correlating language styles, tweeting frequency and participating users. Social network analysis was used to further characterize the local factors in the global social media.

The authors found that the language styles and character types can be used to identify the regions to which the users belong. The authors were able to identify community-specific patterns of communication and reconstruct a social network that exhibits local characteristics.

The results demonstrate that language code can be used to identify the community origin of Chinese tweets. This will enable fine-grain content-based analysis of the Chinese language social media.

The purpose of this paper is to explore how Twitter is used as a political backchannel and potential agenda setter during two televised political debates during the Norwegian election in 2011. The paper engages with current debates about the role of social media in audience participation and traditional media's changing role as gatekeepers and agenda setter.

A combination of quantitative and qualitative methods. By introducing and using the IMSC multiple step analysis model on the Twitter datasets, the authors are able to analyse the flow of thousands of tweets and compare them with topics discussed in the televised debates.

The paper finds that the same topics are discussed on Twitter as on TV, but “the debate about the debate” or Meta talk tweets reveal critical scrutiny of the agenda. The paper identifies a clear pattern of political fandom and media criticism in the “debate about the debate”, indicating that Meta talk in social media can function as a critical public sphere, also in real time, which has not been identified in existing studies of Twitter and political TV shows.

The analysis is unique in the sense that the paper analyses a smaller, national Twitter population in deeper detail than what is common in larger Twitter studies related to political televised debates. The IMSC model can be used in future Twitter studies to uncover layers in the data material and structure the findings.

The purpose of this paper is to introduce Digital Methods Initiative Twitter Capture and Analysis Toolset, a toolset for capturing and analyzing Twitter data. Instead of just presenting a technical paper detailing the system, however, the authors argue that the type of data used for, as well as the methods encoded in, computational systems have epistemological repercussions for research. The authors thus aim at situating the development of the toolset in relation to methodological debates in the social sciences and humanities.

The authors review the possibilities and limitations of existing approaches to capture and analyze Twitter data in order to address the various ways in which computational systems frame research. The authors then introduce the open-source toolset and put forward an approach that embraces methodological diversity and epistemological plurality.

The authors find that design decisions and more general methodological reasoning can and should go hand in hand when building tools for computational social science or digital humanities.

Besides methodological transparency, the software provides robust and reproducible data capture and analysis, and interlinks with existing analytical software. Epistemic plurality is emphasized by taking into account how Twitter structures information, by allowing for a number of different sampling techniques, by enabling a variety of analytical approaches or paradigms, and by facilitating work at the micro, meso, and macro levels.

The paper opens up critical debate by connecting tool design to fundamental interrogations of methodology and its repercussions for the production of knowledge. The design of the software is inspired by exchanges and debates with scholars from a variety of disciplines and the attempt to propose a flexible and extensible tool that accommodates a wide array of methodological approaches is directly motivated by the desire to keep computational work open for various epistemic sensibilities.

The purpose of this paper is to engage in a systematic analysis of academic research that relies on the collection and use of Twitter data, creating topology of Twitter research that details the disciplines and methods of analysis, amount of tweets and users under analysis, the methods used to collect Twitter data, and accounts of ethical considerations related to these projects.

Content analysis of 382 academic publications from 2006 to 2012 that used Twitter as their primary platform for data collection and analysis.

The analysis of over 380 scholarly publications utilizing Twitter data reveals noteworthy trends related to the growth of Twitter-based research overall, the disciplines engaged in such research, the methods of acquiring Twitter data for analysis, and emerging ethical considerations of such research.

The findings provide a benchmark analysis that must be updated with the continued growth of Twitter-based research.

The research is the first full-text systematic analysis of Twitter-based research projects, focussing on the growth in discipline and methods as well as its ethical implications. It is of value for the broader research community currently engaged in social media-based research, and will prompt reflexive evaluation of what research is occurring, how it is occurring, what is being done with Twitter data, and how researchers are addressing the ethics of Twitter-based research.

The purpose of this paper is to analyze the tweeting behavior of 37 astrophysicists on Twitter and compares their tweeting behavior with their publication behavior and citation impact to show whether they tweet research-related topics or not.

Astrophysicists on Twitter are selected to compare their tweets with their publications from Web of Science. Different user groups are identified based on tweeting and publication frequency.

A moderate negative correlation (ρ=−0.339) is found between the number of publications and tweets per day, while retweet and citation rates do not correlate. The similarity between tweets and abstracts is very low (cos=0.081). User groups show different tweeting behavior such as retweeting and including hashtags, usernames and URLs.

The study is limited in terms of the small set of astrophysicists. Results are not necessarily representative of the entire astrophysicist community on Twitter and they most certainly do not apply to scientists in general. Future research should apply the methods to a larger set of researchers and other scientific disciplines.

To a certain extent, this study helps to understand how researchers use Twitter. The results hint at the fact that impact on Twitter can neither be equated with nor replace traditional research impact metrics. However, tweets and other so-called altmetrics might be able to reflect other impact of scientists such as public outreach and science communication.

To the best of the knowledge, this is the first in-depth study comparing researchers’ tweeting activity and behavior with scientific publication output in terms of quantity, content and impact.

The purpose of this paper is twofold. First, it investigates the relationship between television, its audiences and Twitter around the creation of social TV events. Here it contributes to knowledge by charting usage in relation to different types of programmes and by comparing Twitter to Facebook data. Second, it evaluates the way in which student-led research can be used to conduct audience studies with the help of Twitter.

The research applies a quantitative approach, measuring the volume of Twitter messages before, during and after two different types of television programmes, i.e. Reality TV (The X Factor and The Only Way is Essex) and sports broadcasts (football and Formula One). Brief comparisons are also drawn with data collected from Facebook. The pedagogical evaluation of the research is based on self-reflection by the author/tutor.

The research established similar trends and patterns of viewer engagement for both types of television programming, with key activity during and towards the end of a broadcast which points to viewers using Twitter, or Facebook, while watching the event. The findings are compared to previous studies on television programmes and Twitter use. The study also identified that student research using Twitter can lead to a valuable learning experience as it allows students to use their own knowledge of social media to inform the research process.

This research makes a contribution to the small yet growing body of studies examining Twitter activity in relation to TV events. It also contributes to knowledge on the educational use of social media by providing an account of how Twitter can be applied as a research tool by students.

The purpose of this paper is to explore the research status and development trend of the field of event detection in social media (ED in SM) through a bibliometric analysis of academic publications.

First, publication distributions are analyzed including the trends of publications and citations, subject distribution, predominant journals, affiliations, authors, etc. Second, an indicator of collaboration degree is used to measure scientific connective relations from different perspectives. A network analysis method is then applied to reveal scientific collaboration relations. Furthermore, based on keyword co-occurrence analysis, major research themes and their evolutions throughout time span are discovered. Finally, a network analysis method is applied to visualize the analysis results.

The area of ED in SM has received increasing attention and interest in academia with Computer Science and Engineering as two major research subjects. The USA and China contribute the most to the area development. Affiliations and authors tend to collaborate more with those within the same country. Among the 14 identified research themes, newly emerged themes such as Pharmacovigilance event detection are discovered.

This study is the first to comprehensively illustrate the research status of ED in SM by conducting a bibliometric analysis. Up-to-date findings are reported, which can help relevant researchers understand the research trend, seek scientific collaborators and optimize research topic choices.