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Approaching Completeness: Capturing a Hashtagged Twitter Conversation and its Follow-On Conversation
University of Borås, Faculty of Librarianship, Information, Education and IT. (Social media studies)ORCID iD: 0000-0003-0659-4754
University of Borås, Faculty of Librarianship, Information, Education and IT. (Social media studies)ORCID iD: 0000-0001-9228-9179
2015 (English)In: Social science computer review, ISSN 0894-4393, E-ISSN 1552-8286Article in journal (Refereed) Published
Abstract [en]

The aim of this article is to engage with problems of sampling and completeness currently discussed within data science through the specific example of conversations in Twitter. Some of the difficulties involved in Twitter concern restrictions laid out by platform owners, restrictions that make it difficult for researchers to collect complete conversations. A contribution is made through the development of a method for collecting and analyzing follow-on conversations around a set of hashtags. This was made possible through the simultaneous tracking of a set of hashtags and prominent participants in the conversation. The full set of tweets was compared to the subset of tweets including either of the selected hashtags. Including follow-on conversation increased the set of tweets by 56% and the set of tweeting users by 17%. It is also shown that different network analysis techniques and filtering options give different results with regard to prominent users.

Place, publisher, year, edition, pages
Sage Publications, 2015.
Keyword [en]
Twitter, Twitter API, methodology, sampling, conversations, hashtags, selection bias
National Category
Computer and Information Science
Research subject
Library and Information Science
Identifiers
URN: urn:nbn:se:hb:diva-835DOI: 10.1177/0894439315607018OAI: oai:DiVA.org:hb-835DiVA: diva2:857952
Available from: 2015-09-30 Created: 2015-09-30 Last updated: 2016-09-06
In thesis
1. Following Tweets Around: Informetric methodology for the Twittersphere
Open this publication in new window or tab >>Following Tweets Around: Informetric methodology for the Twittersphere
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The purpose of this thesis is to critically discuss methods to collect and analyse data related to the interaction and content on the social platform Twitter. The thesis contains examples of how networked communication can be studied on Twitter, based on the affordances of the platform considering interaction with interfaces and other users. The foundational problem is that social science Twitter research has been based on easily accessible data without introducing or discussing criteria for collecting appropriate samples for a given research task.The thesis builds on one literature review and four studies of political Twitter communication. The analyses are based on a view of the Twitter platform as a non-neutral filtering gatekeeper. On the one hand, Twitter treats content and users asymmetrically, by emphasising the popular. On the other hand, Twitter determines what data are available and how data can be accessed through the API (application programming interface). How Twitter provides access to the data in turn affects the analyses the researcher does. The central problem of the thesis is that researchers do not know what relevant data are not collected. Data collection based on keywords, hashtags or users creates data sets that contain fragments of conversations. To solve the problem, a new method was developed. By combining the hashtag and user-based methods, replies to collected tweets were stored, regardless if they contained a tracked hashtag or not.The four studies this thesis builds on show a complexity of collecting and analysing Twitter data. A key finding is that conversations beyond the hashtag can be quite extensive. As a consequence of this, communication networks based on hashtagged replies were found to be potentially very different from networks based on replies from a more complete data set, where non-hashtagged replies are also included. A network based on hashtagged communication is thus misleading compared to a complete communication network.Apart from that it is not entirely trivial to identify the parameters to define what should be studied; tests of the API showed that complete data sets cannot be obtained. Therefore, it is important to reflect on both the data collected and the data excluded, not only as a result of the sampling criteria but also what is not given access to. It is also important to be clear about the affordances for interaction that exist when the study is made, both in the user interface but also what API allows and permits.This research contributes with knowledge about how Twitter is used in the context being studied, but the main contribution is methodological. With the method developed, collection of more complete data sets is enabled, as is analysis of the conversations that take place on the platform. This results in more accurate measurements of the activity. Based on the results of this thesis, there are reasons to suspect that previous studies could differ in terms of results such as communication network size and shape, as well as the type of users that emerges as prominent in the material, compared to if replies that do not contain the studied hashtag had been collected.

Place, publisher, year, edition, pages
Borås: Högskolan i Borås, 2016. 151 p.
Series
Skrifter från Valfrid, ISSN 1103-6990 ; 61
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-9339 (URN)978-91-981653-0-2 (ISBN)978-91-981653-1-9 (ISBN)
Public defence
2016-10-03, C203, Allégatan 1, Borås, 13:00
Note

Due to copyright, the articles included in this PhD thesis are not available in the digital version of the thesis. Find links to the published articles in the list of papers below.

The article: Lorentzen, D. G. (manuscript). Is it all about politics? A hashtag analysis of the activities of the Swedish political Twitter elite. Is not yet submitted to a journal and is only found in the printed version.

Available from: 2016-09-06 Created: 2016-03-09 Last updated: 2017-01-20Bibliographically approved

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Publisher's full texthttp://ssc.sagepub.com/content/early/2015/09/29/0894439315607018.abstract

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