Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Twitter conversation dynamics of political controversies: The case of Sweden's December Agreement
University of Borås, Faculty of Librarianship, Information, Education and IT. (Social media studies)ORCID iD: 0000-0003-0659-4754
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.

Place, publisher, year, edition, pages
2016. Vol. 21, no 2, SM3
Keyword [en]
Twitter, conversations, politics, information behaviour, content analysis
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
URN: urn:nbn:se:hb:diva-10659OAI: oai:DiVA.org:hb-10659DiVA: diva2:958114
Conference
Social Media Studies Symposium, University of Borås, 15 September, 2015
Available from: 2016-09-06 Created: 2016-09-06 Last updated: 2016-11-17Bibliographically approved
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

Open Access in DiVA

No full text

Other links

http://www.informationr.net/ir/21-2/SM3.html

Search in DiVA

By author/editor
Lorentzen, David
By organisation
Faculty of Librarianship, Information, Education and IT
In the same journal
Information research
Information Studies

Search outside of DiVA

GoogleGoogle Scholar

Total: 496 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf