Course:LIBR559A/Parra, D. et al. (2016)

Citation

Editing Parra, D., Trattner, C., Gómez, D., Hurtado, M., Wen, X., & Lin, Y. R. (2016). Twitter in academic events: a study of temporal usage, communication, sentimental and topical patterns in 16 computer science conferences. Computer Communications,73-301-314

Purpose of article

This article aimed at analyzing how Twitter had been used for communication purposes across scientific events (eg. Conference) over time. In addition, the authors wanted to discover some community characters (such as topic trend and sentiments) of Twitter communication during scientific events as well.

Main Argument(s) and supporting evidence

This article addresses its findings based on analyzing the dataset over the 5 years collected by Topsy API, including the tweets and retweets that contain the conferences’ official hashtags, as well as the participants’ Twitter content posted within the same time period. Accordingly, the authors found out that there was a tendency to shift the Twitter application from conversational usage to informational usage, since more and more conference participants retweet and put external URL on their Twitter. In addition, they found out that there was an increase in participation over time, and it was possible to group the tweets into clusters based on topics of the conferences. What’s more, they found out that conferences differed regards to sentiment expressions. Last but not least, continuing to use hashtags and possessing a central position in the conversation could encourage users in keep using Twitter in the conferences.

Methods

This article was based on case studies, since it used the data collected from the 16 computer science conferences over 5 years to represent how participants behave in scientific events on Twitter.

Areas / Topics / Keywords

Twitter, academic conference, sentiment analysis, and evolution over time.

The term “academic conference” is limited to conferences within the field of computer science in this article; while sentiment analysis referred to how participants express themselves using Twitter during these events, and evolution over time was used to describe the change of participants’ communication mode, the content they post, etc., over the years (from 2009 to 2013) reflected by the content of the tweets related to these 16 conferences.

Theoretical frameworks

Before this study, most previous studies on the application of Twitter during scientific events were based on a small dataset (1 or 2 conferences) that had been collected for a certain year. This article was based on the dataset collected from 16 computer science conferences over 5 years (during 2009 ~2013), which made it the first study that showed the change of Twitter usage over time. In this article, the authors pointed out how Twitter’s conference usage drifted from conversational (replies and comments) to informational (retweets) networks.

Weakness

However, there are some limitations of the data collection process: most content was collected based on the official hashtag, which would leave out some relevant tweets that were not tweeted under these hashtags. What's more, although gathered data from 16 conferences over 5 years, the research sample of this article only include those conferences in the field of computer science, which can't represent the situation of most academic events. Therefore, to make sure that conferences within different areas are also included, the authors could also collect data from conferences in Information Science, STEM areas, social studies, etc., to get a more comprehensive dataset to analyze.

Potential Contribution to Social Studies of Libraries and Librarianship

From my perspective, the method of this article could be used to conduct a research on conferences in the library field as well (such as BCLA). A thorough research on how do librarians using Twitter in academic conferences over the years could be interesting, and guide libraries on how to improve their behavior on using Twitter for communication and promotion.

Page Author: Wendy Zhang