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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 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 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 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.

Marit Kristine Ådland is a Ph.D. student at Oslo and Akershus University College of Applied Science. Her research interests and activity is within knowledge organization, information behavior, information retrieval, and information architecture. Her current research explores users’ tags and tagging behavior in the field of cancer information. She teaches classification and indexing to students training in librarianship.