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Following Tweets Around: Informetric methodology for the Twittersphere
University of Borås, Faculty of Librarianship, Information, Education and IT.ORCID iD: 0000-0003-0659-4754
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.
Series
Skrifter från Valfrid, ISSN 1103-6990 ; 61
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
URN: urn:nbn:se:hb:diva-9339ISBN: 978-91-981653-0-2ISBN: 978-91-981653-1-9 (pdf)OAI: oai:DiVA.org:hb-9339DiVA: diva2:910646
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: 2016-09-12Bibliographically approved
List of papers
1. Polarisation in Political Twitter Conversations
Open this publication in new window or tab >>Polarisation in Political Twitter Conversations
2014 (English)In: Aslib Journal of Information Management, ISSN 2050-3806, Vol. 66, no 3, 329-341 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: 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.

Design/methodology/approach: 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.

Findings: 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.

Originality/value: 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.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2014
Keyword
Twitter, Social network analysis, Sweden, Polarization, Political debate
National Category
Computer and Information Science
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-833 (URN)10.1108/AJIM-09-2013-0086 (DOI)
External cooperation:
Available from: 2015-09-30 Created: 2015-09-30 Last updated: 2016-09-06Bibliographically approved
2. Approaching Completeness: Capturing a Hashtagged Twitter Conversation and its Follow-On Conversation
Open this publication in new window or tab >>Approaching Completeness: Capturing a Hashtagged Twitter Conversation and its Follow-On Conversation
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
Twitter, Twitter API, methodology, sampling, conversations, hashtags, selection bias
National Category
Computer and Information Science
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-835 (URN)10.1177/0894439315607018 (DOI)
Available from: 2015-09-30 Created: 2015-09-30 Last updated: 2016-09-06
3. Twitter conversation dynamics of political controversies: The case of Sweden's December Agreement
Open this publication in new window or tab >>Twitter conversation dynamics of political controversies: The case of Sweden's December Agreement
2016 (English)In: Information research, ISSN 1368-1613, E-ISSN 1368-1613, Vol. 21, no 2, SM3Article in journal (Refereed) Published
Abstract [en]

Introduction. Following the news of an extraordinary agreement between six political parties, intense discussions on Twitter took place, suitable for investigation of political controversies on the platform. The purpose is to analyse threaded conversations on Twitter in relation to this political event.

Method. By using the streaming API with a set of hashtags and the most active participants in the conversations, tweets related to the event and tweets belonging to the follow-on conversation were captured. From this set, the replies were used to build conversational threads.

Analysis. The dataset was analysed using both quantitative and qualitative methods. The overall lifecycle of the conversations was outlined using statistical methods. Ten conversational threads were studied using qualitative content analysis.

Results. Immediately after the agreement, activity was focused on information diffusion, but following this, discussions emerged. Politicians were frequently talked to but rarely replied to tweets directed to them. Citizens from the general public dominated the activity.

Conclusions. Conversations do exist beyond the hashtag but few examples of democratic debate were found. Conversations are more likely to develop within tightly knit groups followership-wise. Echo chambers as well as discussions where non like-minded argued were identified. Consensus formation was not common.

Keyword
Twitter, conversations, politics, information behaviour, content analysis
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-10659 (URN)
External cooperation:
Conference
Social Media Studies Symposium, University of Borås, 15 September, 2015
Available from: 2016-09-06 Created: 2016-09-06 Last updated: 2016-09-06
4. Webometrics benefitting from web mining? An investigation of methods and applications of two research fields
Open this publication in new window or tab >>Webometrics benefitting from web mining? An investigation of methods and applications of two research fields
2014 (English)In: Scientometrics, ISSN 0138-9130, E-ISSN 1588-2861, Vol. 99, no 2Article in journal (Refereed) Published
Abstract [en]

This is a cross-field literature review and comparison of the fields webometrics (cybermetrics) and web (data) mining.

Place, publisher, year, edition, pages
Akademiai Kiado Rt., 2014
Keyword
webometrics, web mining, cybermetrics, web data mining, literature review, interdisciplinary studies
National Category
Computer and Information Science Social Sciences Interdisciplinary Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-1748 (URN)10.1007/s11192-013-1227-x (DOI)000334277800011 ()2320/13196 (Local ID)2320/13196 (Archive number)2320/13196 (OAI)
External cooperation:
Available from: 2015-11-13 Created: 2015-11-13 Last updated: 2016-09-06Bibliographically approved

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