Det här kapitlet handlar om bokläsning i Sverige under 2022, och hjälper oss följa hur läsvanor förändras över tid. Vi kan bland annat se att andelen som säger att de läst någon bok under året ligger på den lägsta nivån sedan mätningen började 1995.Framför allt verkar män ha minskat sin läsning av tryckta böcker. Ljudböcker är det enda bokformat som ökat i användning under 2022. Samtidigt ser vi att unga vuxna 16–29 år fortsätter visa stort intresse för läsning efter sin markanta ökning i tryckt bokläsning från föregående år. I den yngsta åldersgruppen har det nu även skett en betydande ökning av ljudboksläsning. När det gäller hur läsare får tag på sina böcker, kan vi bland annat se en ökning av personer som köpte tryckta böcker via fysisk bokhandel, även om siffrorna inte är tillbaka på samma nivå som tiden före pandemin. I kapitlet resonerar vi kring 2022 års statistik och vad förändringar i läsvanor kan bero på.

Purpose: The purpose of this paper is to investigate practices of argumentation on Twitter discussions about climate change.

Design/methodology/approach: Conversational threads were collected from the Twitter API. Fundamental concepts from argumentation theory and linking practices were operationalised through a coding schema for content analysis. Tweets were analysed in the context of the discussions and coded according to their argumentative approach, interaction type and argumentation stage. Linked and embedded sources were analysed in order to find how they were used in arguments, the plausibility and soundness of the message, the consistency and trustworthiness of the linked source and its adequacy with the target audience.

Findings: Among the interactions between arguers, this study found five typical practices and several patterns involving the dynamics of the conversations, the strategy of the argumentation and the linking practices. Although the rhetorical approach was prominent, the agreement was rarely achieved. The arguers used a variety of sources to justify or support their positions, often embedding non-textual content. These linking practices, together with the strategy adopted and the topics discussed, suggest the involvement of a multiple audience engaged in discussing ad lib scientific artefacts, topics and outputs.

Originality/value: While Twitter has been the focus for many research papers, the conversational threads have been given little attention so far. With the Twitter API making conversations more accessible for research, this paper does not only give insight into multiple audience group argumentation dynamics but also provides a method to study the conversations from an argumentation theory perspective.

Introduction. A method for studying use of scientific sources in arguments on Twitter is demonstrated.

Method. Data were collected from the Twitter API v. 2.0 using Focalevents, searching for tweets with links to DOIs, and then collecting conversations around these tweets. Analysis. Three conversations on different topics were analysed searching for argumentative behaviour, use of scientific sources, their reliability, consistency and adequacy in relation to the argument and the target audience. Both quantitative and qualitative content analysis based on argumentation theory were applied.

Results. The method allowed us to identify scientific publications used argumentatively by a multiple audience in the context of Twitter conversations. The publications were used to build scientific arguments, mainly, but not exclusively, from individual and collegial expert opinion. Scientific findings were often misinterpreted and used improperly to the benefit of the argument.

Conclusions. Through the use of argumentation theory to study conversations in a structured way, the paper demonstrates how to approach the usage of scientific publications in arguments. Scientific publications were used to build scientific arguments from different types of expert opinion, for giving proofs for claims and counter-arguments, and inconsistent or biased arguments from individual expert opinion.

I det här kapitlet undersöker vi bokläsning i Sverige under 2021. Vi jämför läsningav de tre olika formaten tryckta böcker, ljudböcker och e-böcker i olika grupper. Vistuderar också högläsning för barn, samt varifrån människor får tag på sina böcker.Den nationella SOM-undersökningen för 2021 visar att läsning av alla tre bokfor-maten har ökat under året, vilket skulle kunna bero på pandemin. Särskilt intressantär att andelen unga vuxna 16–29 år som läst tryckta böcker har ökat tydligt sedan2020. Samtidigt ser högläsning för barn ut att ha minskat något under 2021. Underpandemiåren 2020–2021 har färre personer köpt böcker i fysisk bokhandel, ochandelen som lånat tryckta böcker via bibliotek minskade också under 2021. Inköpvia nätbokhandel har ökat, och något fler har också lånat digitala böcker via bibliotekeller strömmat dem via prenumerationstjänster. I kapitlet resonerar vi kring åretsförändringar och vad de kan bero på.

Purpose – The purpose of the paper is to analyse the interactions of bridging users in Twitter discussionsabout vaccination.

Design/methodology/approach – Conversational threads were collected through filtering the Twitterstream using keywords and the most active participants in the conversations. Following data collection andanonymisation of tweets and user profiles, a retweet network was created to find users bridging the mainclusters. Four conversations were selected, ranging from 456 to 1,983 tweets long, and then analysed throughcontent analysis.

Findings – Although different opinions met in the discussions, a consensus was rarely built. Many subthreadsinvolved insults and criticism, and participants seemed not interested in shifting their positions.However, examples of reasoned discussions were also found.

Originality/value – The study analyses conversations on Twitter, which is rarely studied. The focus on theinteractions of bridging users adds to the uniqueness of the paper.

Kapitlet behandlar läsning av böcker i olika format; tryckta böcker, e-böcker och ljudböcker, bland män och kvinnor i relation till ålder, bostadsort och utbildnings-nivå. Vi undersöker hur årets siffror ställer sig gentemot föregående års nationella SOM-undersökningar. Läsning av ljudböcker 2020 ökar mest i jämförelse med 2019, som var ett mellanår för ljudboken. Föräldrars högläsning för barn har minskat med tre procentenheter under 2020 jämfört med 2019. Detta trots ökad hemmatillvaro p.g.a. den pågående pandemin. Den främsta källan för att få tag på tryckta böcker är fortsatt bokhandel trots en minskning med 6 procentenheter sedan året före. Prenumerationstjänster är det vanligaste sättet att få tillgång till ljudböcker medan e-böcker skaffas i stort sett i lika stor utsträckning via prenumerationstjänster som via bibliotek och nätbokhandel. Intressant att notera är att nedladdningen av e-böcker har ökat både hos biblioteken och prenumerationstjänsterna trots att läsning av e-böcker endast har ökat med en procentenhet både när det gäller läsning ofta och någon gång per år.

Detta kapitel introducerar nätverksanalys som ett sätt att studera användaraktivitet och relationer i digitala miljöer utifrån exemplet Twitter. Vad betyder de olika strukturerna som kan ses i ett nätverk? Vad betyder det att vissa delar och vissa punkter i ett nätverk är mer framträdande än andra? Och vad betyder de olika nätverksmåtten i relation till vilka punkter som är viktigast för olika syften? Detta är frågor som kapitlet avser att besvara. Därutöver resoneras i kapitlet om vilken kunskap som kan erhållas genom studier av en plattform (som Twitter) utifrån dess egenskaper, begränsningar och möjligheter, samt den urvals- och filtreringsproblematik som uppstår i samband med studier av digitala miljöer.

Kapitlet behandlar läsning av böcker i olika format bland kvinnor och män samt hur ålder, utbildningsnivå och bostadsort påverkar i vilken utsträckning man läser. Vi undersöker hur årets siffror ställer sig gentemot föregående års nationella SOM-undersökningar. Vi noterar i årets undersökning att läsning av böcker någon gång per år fortsatt ligger högt och att de som läser mest återigen är högutbildade kvin-nor som bor i en storstad. Läsning av digitala böcker ökar med någon procentenhet men lyssning av ljudböcker har saktat in och ökar inte i samma utsträckning som tidigare år. Det är de yngre (16–29 år) som läser mest digitala böcker och med sti-gande ålder ser vi att den digitala läsningen minskar. Biblioteken är populära för lån av böcker men vanligast är att tryckta böcker införskaffas via fysisk bokhandel eller lånas eller fås av familj eller vänner och digitala böcker införskaffas i första hand via prenumerationstjänster.

Under det gångna året har bibliotek särskilt grundligt diskuterats på olika håll i biblioteks-Sverige. Upprinnelsen till diskussionen är det förslag till nationell biblioteksstrategi som presenterats under året. Många olika intressen skall bevakas inom ramen för denna biblioteksstrategi och i detta kapitel uppmärksammas några av dem som biblioteken har betydelse för. Vi ägnar först intresse åt bibliotekens höglitare och därefter åt bibliotekens besökare. Ifråga om besökare så besöker boende i glesbygd bibliotek mest sällan, och lågutbildade mindre än högutbildade. Bland biblioteksbesökare finns alla åldrar representerade, och yngre visar sig besöka bibliotek mer än vad äldre gör. Avslutningsvis tar vi fasta på äldre på bibliotek, både som litare och som besökare.

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.

In this study, we investigate different strategies for assigning MeSH (Medical Subject Headings) terms to clinical guidelines using machine learning. Features based on words in titles and abstracts are investigated and compared to features based on topics assigned to references cited by the guidelines. Two of the feature engineering strategies utilize word embeddings produced by recent models based on in the distributional hypothesis, called word2vecand fastText. The evaluation results show that reference-based strategies tend to yield a higher recall and F1 scores for MeSH terms with a sufficient amount of training instances, whereas title and abstract based features yield a higher precision.

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.

Purpose: The purpose of this paper is to map the topics discussed over three four week periods among a set of predefined Twitter users.

Method: 985 Twitter users were selected from an eight week pilot study of conversations around a political hashtag. These were tracked for a total of twelve weeks during one year. The hashtags in tweets posted by and to these users were analysed with regards to co-occurrences and trends.

Findings: Overall, political topics dominated the activities of and around the Twitter elite. Differences between usage of hashtags could be seen when considering only tweets posted by the tracked users compared to when considering all tweets in the dataset. The 258 most often used hashtags were closely related to most other prominent hashtags.

Originality: This longitudinal study sheds light over how topics and hashtags evolve over time.

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.

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.

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.

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.

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.

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

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.