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Gunnarsson Lorenzen, DavidORCID iD iconorcid.org/0000-0003-0659-4754
Alternative names
Publications (10 of 11) Show all publications
Wallin, B., Tattersall Wallin, E. & Gunnarsson Lorenzen, D. (2019). Bokläsning och den svenska bokmarknaden. In: Ulrika Andersson, Björn Rönnerstrand, Patrik Öhberg & Annika Bergström (Ed.), Storm och stiltje: . Göteborg: Göteborgs universitet: SOM-institutet
Open this publication in new window or tab >>Bokläsning och den svenska bokmarknaden
2019 (Swedish)In: Storm och stiltje / [ed] Ulrika Andersson, Björn Rönnerstrand, Patrik Öhberg & Annika Bergström, Göteborg: Göteborgs universitet: SOM-institutet , 2019Chapter in book (Other academic)
Abstract [sv]

Det här kapitlet behandlar frågor som på olika sätt rör böcker, bokläsning och distri-bution av e-litteratur på den svenska bokmarknaden. Exempelvis analyseras hur stor andel av svenska folket som läser böcker, i vilka format de läser, och hur ofta de läser. Olika samhällsgruppers läsvanor analyseras, liksom hur läsningen har förändrats över tid. Några av de resultat som framkommer är att läsning av e-böcker fortsätter öka. Andelen som läser e-fackböcker har ökat från 13 till 16 procent mellan 2017 och 2018 samtidigt som andelen läsare av e-skönlitteratur har ökat från 16 till 18 procent. Lyssning av ljudböcker har ökat för facklitteratur från 9 till 14 procent medan lyss-ning av skönlitteratur har ökat från 26 till 29 procent. Statistik från bokbranschen tyder på att allt fler använder sig av prenumerationstjänster för sin konsumtion av digitala böcker, vilket är en fråga som kommer att diskuteras i kapitlet tillsammans med tillgången till digitala böcker via folkbibliotek och bokhandel.

Place, publisher, year, edition, pages
Göteborg: Göteborgs universitet: SOM-institutet, 2019
Keywords
Digital läsning, bokläsning, e-böcker, ljudböcker, tryckta böcker, den svenska bokmarknaden, folkbibliotek
National Category
Other Social Sciences not elsewhere specified
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-21275 (URN)
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-07-29Bibliographically approved
Gunnarsson Lorenzen, D., Eklund, J., Nelhans, G. & Ekström, B. (2019). On the potential for detecting scientific issues and controversies on Twitter: A method for investigation conversations mentioning research. In: Proceedings of ISSI.: . Paper presented at ISSI, the 17th International Conference on Scientometrics & Informetrics, Rome, 2-5 September, 2019. (pp. 2189-2198). , Article ID 375.
Open this publication in new window or tab >>On the potential for detecting scientific issues and controversies on Twitter: A method for investigation conversations mentioning research
2019 (English)In: Proceedings of ISSI., 2019, p. 2189-2198, article id 375Conference paper, Published paper (Refereed)
Abstract [en]

In this study, we demonstrate how to collect Twitter conversations emanating from or referring to scientific papers. We propose segmenting the conversational threads into smaller segments and then compare them using information retrieval techniques, in order to find differences and similarities between discussions and within discussions. While the method still can be improved, the study shows that it is possible to collect larger conversations about research on Twitter, and that these are suitable for various automated methods. We do however identify a need to analyse these with qualitative methods as well.

Keywords
Twitter, conversations
National Category
Computer and Information Sciences
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-21908 (URN)
Conference
ISSI, the 17th International Conference on Scientometrics & Informetrics, Rome, 2-5 September, 2019.
Projects
Data4Impact
Available from: 2019-10-31 Created: 2019-10-31 Last updated: 2019-11-05Bibliographically approved
Gunnarsson Lorenzen, D. (2018). Discussing research on Twitter: Measuring the conversational impact of scientific publications. In: : . Paper presented at 23rd Nordic Workshop on Bibliometrics and Research Policy, Borås, 8-9 November, 2018..
Open this publication in new window or tab >>Discussing research on Twitter: Measuring the conversational impact of scientific publications
2018 (English)Conference paper, Poster (with or without abstract) (Other academic)
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-15858 (URN)
Conference
23rd Nordic Workshop on Bibliometrics and Research Policy, Borås, 8-9 November, 2018.
Projects
Data4Impact
Funder
EU, Horizon 2020, 770531
Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-03-05Bibliographically approved
Gunnarsson Lorentzen, D. (2016). Following Tweets Around: Informetric methodology for the Twittersphere. (Doctoral dissertation). Borås: Högskolan i Borås
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. p. 151
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
Lorentzen, D. (2016). Twitter conversation dynamics of political controversies: The case of Sweden's December Agreement. Paper presented at Social Media Studies Symposium, University of Borås, 15 September, 2015. Information research, 21(2), Article ID SM3.
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, article id 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.

Keywords
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)
Conference
Social Media Studies Symposium, University of Borås, 15 September, 2015
Available from: 2016-09-06 Created: 2016-09-06 Last updated: 2017-11-21Bibliographically approved
Nelhans, G. (2016). Twitter conversation patterns related to research papers. Paper presented at Selected papers from the Social Media Studies Symposium, University of Borås, 15 September, 2015. Information research, 21(2), Article ID SM2.
Open this publication in new window or tab >>Twitter conversation patterns related to research papers
2016 (English)In: Information research, ISSN 1368-1613, E-ISSN 1368-1613, Vol. 21, no 2, article id SM2Article in journal (Refereed) Published
Abstract [en]

Introduction. This paper deals with what academic texts and datasets are referred to and discussed on Twitter. We used document object identifiers as references to these items. Method. We streamed tweets from the Twitter application programming interface including the strings "dx" and "doi" while simultaneously streaming tweets posted by and to the authors of the tweets captured. By doing so we were able to capture tweets referring to a digital object as well as the replies to these tweets. Analysis. The captured tweets were analysed in different ways, both quantitatively and qualitatively. 1) Bibliometric analyses were made on the digital object identifiers, 2) the thirty of thesee most mentioned and retweeted were analysed and 3) the conversations with at least ten tweets were analysed using content analysis. Results. Research from the natural sciences was most prominent, as was research published in open access journals. Different types of conversations relating to the digital objects were found, both when looking at them qualitative and their visual structure in terms of nodes and arcs. The conversations involved academics but were not always academic in nature. Conclusions. Digital object identifiers were mainly referred to for self-promotion, as conversation starters or as arguments in discussions.

Keywords
altmetrics, twitter conversation, Gephi, VOSviewer, qualitative, DOI
National Category
Other Social Sciences not elsewhere specified
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-10714 (URN)
Conference
Selected papers from the Social Media Studies Symposium, University of Borås, 15 September, 2015
Available from: 2016-09-19 Created: 2016-09-19 Last updated: 2017-11-21Bibliographically approved
Lorentzen, D. & Nolin, J. (2015). Approaching Completeness: Capturing a Hashtagged Twitter Conversation and its Follow-On Conversation. Social science computer review, 35(2), 277-286
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 1552-8286, Vol. 35, no 2, p. 277-286Article 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
Keywords
Twitter, Twitter API, methodology, sampling, conversations, hashtags, selection bias
National Category
Computer and Information Sciences
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: 2018-06-14Bibliographically approved
Lorentzen, D. (2014). Polarisation in Political Twitter Conversations. Aslib Journal of Information Management, 66(3), 329-341
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, p. 329-341Article 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
Keywords
Twitter, Social network analysis, Sweden, Polarization, Political debate
National Category
Computer and Information Sciences
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: 2018-01-11Bibliographically approved
Gunnarsson Lorentzen, D. (2014). Webometrics benefitting from web mining? An investigation of methods and applications of two research fields. Scientometrics, 99(2)
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
Keywords
webometrics, web mining, cybermetrics, web data mining, literature review, interdisciplinary studies
National Category
Computer and Information Sciences 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: 2018-01-10Bibliographically approved
Lorentzen, D. (2014). Webometrics benefitting from web mining?: An investigation of methods and applications of two research fields. Scientometrics, 99(2), 409-445
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, ISSN 0138-9130 1588-2861, Vol. 99, no 2, p. 409-445Article in journal (Refereed) Published
Abstract [en]

Webometrics and web mining are two fields where research is focused on quantitative analyses of the web. This literature review outlines definitions of the fields, and then focuses on their methods and applications. It also discusses the potential of closer contact and collaboration between them. A key difference between the fields is that webometrics has focused on exploratory studies, whereas web mining has been dominated by studies focusing on development of methods and algorithms. Differences in type of data can also be seen, with webometrics more focused on analyses of the structure of the web and web mining more focused on web content and usage, even though both fields have been embracing the possibilities of user generated content. It is concluded that research problems where big data is needed can benefit from collaboration between webometricians, with their tradition of exploratory studies, and web miners, with their tradition of developing methods and algorithms.

Place, publisher, year, edition, pages
Akademiai Kiado, 2014
Keywords
webometrics, web mining, cybermetrics, web data mining, literature review, interdisciplinary studies
National Category
Computer and Information Sciences
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-832 (URN)10.1007/s11192-013-1227-x (DOI)
Available from: 2015-09-30 Created: 2015-09-30 Last updated: 2018-01-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-0659-4754

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