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Eklund, Johan
Publications (10 of 22) Show all publications
Eklund, J. & Nelhans, G. (2024). SOU Explorer: An analysis platform for explorations ofhow research is cited and used in official reports of theSwedish Government. In: Proceedings of the Huminfra Conference (HiC 2024): . Paper presented at HUMINFRA (HiC-2024), Gothenburg, January 10-11, 2024 (pp. 21-21).
Open this publication in new window or tab >>SOU Explorer: An analysis platform for explorations ofhow research is cited and used in official reports of theSwedish Government
2024 (English)In: Proceedings of the Huminfra Conference (HiC 2024), 2024, p. 21-21Conference paper, Oral presentation with published abstract (Refereed)
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-31455 (URN)
Conference
HUMINFRA (HiC-2024), Gothenburg, January 10-11, 2024
Funder
Swedish Research Council
Note

Finansiär och Projektinformation: Huminfra, VR

Available from: 2024-01-29 Created: 2024-01-29 Last updated: 2024-01-29
Eklund, J. (2023). Book review: Kazakoff, Miro. Persuading with data: a guide to designing, delivering, and defending your data. Cambridge, MA: MIT Press, 2022. [Review]. Information research, 28(1), 116-117, Article ID 536.
Open this publication in new window or tab >>Book review: Kazakoff, Miro. Persuading with data: a guide to designing, delivering, and defending your data. Cambridge, MA: MIT Press, 2022.
2023 (English)In: Information research, E-ISSN 1368-1613, E-ISSN 1368-1613, Vol. 28, no 1, p. 116-117, article id 536Article, book review (Other academic) Published
Place, publisher, year, edition, pages
Borås: University of Borås, 2023
Keywords
book review
National Category
Social Sciences
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-31170 (URN)
Available from: 2024-01-10 Created: 2024-01-10 Last updated: 2024-01-13Bibliographically approved
Lindström Sol, S., Gustrén, C., Nelhans, G., Eklund, J., Johannisson, J. & Blomgren, R. (2022). Mapping research on the social impact of the arts: what characterises the field?. Open Research Europe, 1(124)
Open this publication in new window or tab >>Mapping research on the social impact of the arts: what characterises the field?
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2022 (English)In: Open Research Europe, E-ISSN 2732-5121, Vol. 1, no 124Article in journal (Refereed) Published
Abstract [en]

This article explores the broad and undefined research field of the social impact of the arts. The effects of art and culture are often used as justification for public funding, but the research on these interventions and their effects is unclear. Using a co-word analysis of over 10,000 articles published between 1990 and 2020, we examined the characteristics of the field as we have operationalised it through our searches. We found that since 2015 this research field has expanded and consists of different epistemologies and methodologies, summarised in largely overlapping subfields belonging to the social sciences, humanities, arts education, and arts and health/therapy. In formal or informal learning settings, studies of theatre/drama as an intervention to enhance skills, well-being, or knowledge among children are most common in our corpus. A study of the research front through the bibliographic coupling of the most cited articles in the corpus confirmed the co-word analysis and revealed new themes that together form the ground for insight into research on the social impact of the arts. This article can therefore inform discussions on the social value of culture and the arts. 

National Category
Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-28677 (URN)10.12688/openreseurope.14147.2 (DOI)2-s2.0-85141957447 (Scopus ID)
Funder
EU, Horizon 2020, 870621
Available from: 2022-09-30 Created: 2022-09-30 Last updated: 2024-02-01
Eklund, J. & Nelhans, G. (2022). Probabilistic explorations of citation contexts: Citation roles and subject content of scientific references. In: Robinson-Garcia, N; Torres-Salinas, D; Arroyo-Machado, W (Ed.), Proceedings of the 26th International Conference on Science and Technology Indicators: . Paper presented at 26th International Conference on Science, Technology and Innovation Indicators (STI 2022), Granada, Spain, 7-9 September 2022.
Open this publication in new window or tab >>Probabilistic explorations of citation contexts: Citation roles and subject content of scientific references
2022 (English)In: Proceedings of the 26th International Conference on Science and Technology Indicators / [ed] Robinson-Garcia, N; Torres-Salinas, D; Arroyo-Machado, W, 2022Conference paper, Published paper (Refereed)
Abstract [en]

In this study, we have started to investigate how distinguishing the role of the cited reference from the subject of the cited reference can facilitate a more nuanced way to evaluate the citation context in the referring paper. Using natural language processing methods, we have developed methods to both enrich and distinguish specific traits in the aggregated citances. In future work we intend to extend the present analysis to a larger set of publications from the corpus and to cover more disciplines to be able to evaluate the results more precisely.

National Category
Social Sciences Interdisciplinary Information Studies
Identifiers
urn:nbn:se:hb:diva-28676 (URN)10.5281/zenodo.6957176 (DOI)
Conference
26th International Conference on Science, Technology and Innovation Indicators (STI 2022), Granada, Spain, 7-9 September 2022
Available from: 2022-09-30 Created: 2022-09-30 Last updated: 2022-11-16
Eklund, J. (2021). Book Review: Effective data storytelling: how to drive change with data, narrative and visuals [Review]. Information research, 26(1), Article ID R713.
Open this publication in new window or tab >>Book Review: Effective data storytelling: how to drive change with data, narrative and visuals
2021 (English)In: Information research, E-ISSN 1368-1613, Vol. 26, no 1, article id R713Article, book review (Other (popular science, discussion, etc.)) Published
National Category
Information Studies
Identifiers
urn:nbn:se:hb:diva-26042 (URN)000631430800020 ()
Available from: 2021-07-12 Created: 2021-07-12 Last updated: 2022-02-10Bibliographically approved
Eklund, J., Nelhans, G. & Blomgren, R. (2021). Discursive shifts in the Swedish parliament. In: : . Paper presented at Digital History in Sweden Conference, 2021, Umeå: 9–10 December.
Open this publication in new window or tab >>Discursive shifts in the Swedish parliament
2021 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

This work in progress aims to perform a comprehensive analysis of digital data publicly available from the Swedish parliament, such as motions, interpellations, and protocols from discussions in the plenum. To this end, we will use methods based on computational linguistics, such as topic modeling, word embeddings, and sentiment analysis, to identify prominent discourses corresponding to co-occurrence patterns of the words used. Using data from the early 1970s and onward, this project will involve a chronological examination of semantic and discursive changes with regard to topics such as equality, neutrality, the EU, the monarchy, immigration, climate change, and cultural policy. One research question that will be investigated in relation to this analysis is to what extent discursive changes can be detected within specific political parties, and what historical and political reasons can be posited to underlie these changes.Another research question focuses on scientometric aspects of how scholarly research is used to support claims made in the political discussion. With regard to this question, we will more specifically investigate the conceptual aspects of the texts surrounding citations (so-called citances) which will be mined for information such as what research is referred to in terms of individuals, position, disciplinary affiliations, and active research topics. In these citances, the significant content is often present as latent references that require further elucidation, together with an analysis of the sentiments expressed in the argumentation. This analysis will be further enhanced by investigating the usage of hedge terms that may indicate a level of uncertainty about the cited research.

Keywords
Swedish Parliament, semantic modelling, discursive changes, political issues
National Category
Information Studies Political Science (excluding Public Administration Studies and Globalisation Studies) Language Technology (Computational Linguistics)
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-27111 (URN)
Conference
Digital History in Sweden Conference, 2021, Umeå: 9–10 December
Projects
Data as Impact Lab
Available from: 2021-12-29 Created: 2021-12-29 Last updated: 2022-01-04Bibliographically approved
Nelhans, G. & Eklund, J. (2021). Scientosemantics Of Applied Research Using AI And Machine Learning – A Sequential Approach. Borås
Open this publication in new window or tab >>Scientosemantics Of Applied Research Using AI And Machine Learning – A Sequential Approach
2021 (English)Report (Other academic)
Place, publisher, year, edition, pages
Borås: , 2021. p. 39
National Category
Computer Sciences
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-26526 (URN)
Projects
Data as Impact Lab
Note

Projekt finansierat av Lindholmen Science Park

https://www.hb.se/en/research/research-portal/projects/bibliometric-analysis-and-entity-extraction-for-drive-sweden--ai-sweden/

Available from: 2021-09-24 Created: 2021-09-24 Last updated: 2022-01-11
Nelhans, G. & Eklund, J. (2021). Semantic knowledge discovery. In: : . Paper presented at 26th Nordic Workshop on Bibliometrics and Research Policy (NWB2021), Odense, Denmark, 3-5 november 2021..
Open this publication in new window or tab >>Semantic knowledge discovery
2021 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Since many databases lack relevance ranking, a citation-based approach can be a valuable complement since it is possible to use citation-based data to indicate centrality, relevance, or visibility in the research community. However, using bibliometric methods in the humanities is often challenging since a lot of the research literature is not indexed in the traditional citation databases that we generally use for bibliometric mapping.

 

We introduce a combined bibliometric and semantic approach to extend a network of bibliographic records by incorporating a larger set of records lacking bibliometric features based on the semantic similarities between their titles. In order to expand the set of identified relevant articles, we used the Universal Sentence Encoder (USE) algorithm developed by Google Research to generate semantic vectors for the titles.

 

We searched several different databases, of which some include citation data, to create a pool C of candidate documents within the selected subject area. A set A of documents was obtained from a citation database to generate the initial network of articles. We then calculated the bibliographic coupling of articles as quantified by their shared references. 

 

We manually selected a small set S1 ⊂ A of documents representing different topical clusters as a seed for the expansion based on semantic similarities. For each document d ∈ S1, we ranked the documents in C in ascending order according to their cosine distance to the title vector assigned to d, then selecting the k documents closest to d. This procedure gave us a set S2 ⊂ C of documents to read. 

The results were evaluated using qualitative analysis to determine they were thematically relevant to the present information needs. 

Keywords
citation analysis, machine learning, semantic modelling, bibliographic networks
National Category
Information Studies Language Technology (Computational Linguistics)
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-27158 (URN)
Conference
26th Nordic Workshop on Bibliometrics and Research Policy (NWB2021), Odense, Denmark, 3-5 november 2021.
Projects
Data as Impact Lab
Available from: 2022-01-10 Created: 2022-01-10 Last updated: 2022-01-12Bibliographically approved
Nelhans, G., Eklund, J. & Gunnarsson-Lorentzen, D. (2020). Data as Impact Lab: Hackathon on metascience. In: : . Paper presented at iConference, Borås, Sweden, 23-26 March.
Open this publication in new window or tab >>Data as Impact Lab: Hackathon on metascience
2020 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

Recent medial discussion on “fake-news” underlines the importance of evidence-baseddecision-making. To gather, analyze and interpret “facts” is, however, in our information-densedigital times, not always easy. Activities such as information seeking, knowledge building andevaluation in scholarly practice are often performed using bibliometric/informetric methods.The increased interest in bibliometrics also opens for new questions on how data sources arebeing used and what kind of challenges and/or possibilities that warrant further investigation. In this session for interaction and engagement, we invite participants to explore both means ofanalyzing already available data sources using machine-learning technology, as well as toinclude new sets of data that could augment the different views of grasping research activitiesusing algorithms. Such data could be both content-intensive (as text), time-sensitive (as events), contextual (in terms of links between different properties) or multi-modal, meaning that othersources, such as imagery, sound, and video – even material objects may constitute possiblecontributions as data as impact.

National Category
Information Studies
Identifiers
urn:nbn:se:hb:diva-24585 (URN)
Conference
iConference, Borås, Sweden, 23-26 March
Available from: 2021-01-07 Created: 2021-01-07 Last updated: 2021-01-07Bibliographically approved
Eklund, J., Gunnarsson Lorenzen, D. & Nelhans, G. (2019). MESH classification of clinical guidelinesusing conceptual embeddings of references. In: Giuseppe Catalano, Cinzia Daraio, Martina Gregori, Henk F. Moed and Giancarlo Ruocco (Ed.), Proceedings of the 17th conference of the International society for scientometrics and informetrics, ISSI: with a Special STI Indicators Conference Track. Paper presented at 17th conference of the International society for scientometrics and informetrics, ISSI (pp. 859-864). , 2
Open this publication in new window or tab >>MESH classification of clinical guidelinesusing conceptual embeddings of references
2019 (English)In: Proceedings of the 17th conference of the International society for scientometrics and informetrics, ISSI: with a Special STI Indicators Conference Track / [ed] Giuseppe Catalano, Cinzia Daraio, Martina Gregori, Henk F. Moed and Giancarlo Ruocco, 2019, Vol. 2, p. 859-864Conference paper, Published paper (Refereed)
Abstract [en]

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.

Keywords
MESH, clinical guidelines, machine learning, word embedding, word2vec, fasttext
National Category
Information Studies
Research subject
Library and Information Science
Identifiers
urn:nbn:se:hb:diva-22096 (URN)978-88-3381-118-5 (ISBN)
Conference
17th conference of the International society for scientometrics and informetrics, ISSI
Projects
Data for Impact
Funder
EU, Horizon 2020, 770531
Available from: 2019-11-22 Created: 2019-11-22 Last updated: 2019-12-06Bibliographically approved
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