lnu.sePublications
Change search
Link to record
Permanent link

Direct link
BETA
Kerren, Andreas, Dr.-Ing.ORCID iD iconorcid.org/0000-0002-0519-2537
Publications (10 of 156) Show all publications
Simaki, V., Paradis, C. & Kerren, A. (2019). A two-step procedure to identify stance constructions in discourse from political blogs. Corpora, 14(3)
Open this publication in new window or tab >>A two-step procedure to identify stance constructions in discourse from political blogs
2019 (English)In: Corpora, ISSN 1749-5032, E-ISSN 1755-1676, Vol. 14, no 3Article in journal (Refereed) Accepted
Abstract [en]

The Brexit Blog Corpus (BBC) is a collection of texts extracted from political blogs, which, in a recent study, was annotated according to a cognitive-functional stance framework by two independent annotators (Annotator A and B) using semantic criteria (Simaki et al. 2017). The goal was to label the stance or stances taken based on the overall meaning of a set of utterances. The annotators were not instructed to identify the lexical forms that were used to express the stances. In this study, we make use of those stance labelled utterances as a springboard to approach stance-taking in text from the opposite point of view, namely from how stance is realised through language. Our aim is to provide a description of the specific lexical elements used to express six stance categories, i.e., CONTRARIETY, HYPOTHETICALITY,  NECESSITY, PREDICTION, SOURCE OF KNOWLEDGE, and UNCERTAINTY. To this end, we followed a two-step experimental procedure. First, we performed a quantitative analysis of the stance labelled utterances in order to identify the lexical realisations of each stance category. Second, we carried out a meta-annotation of the data. Annotator B was instructed to single out the actual lexical forms of the constructions that triggered his semantic stance category decisions. This meta-annotation procedure made it possible for us to sift out the most salient lexical realisations of the constructions of each of the six category types on the basis of the qualitative assessments made by Annotator B. We then compared the results of the quantitative and the qualitative approaches, and we present a list of shared stance expressions for each stance category type.

Keywords
stance-taking, social media text analysis, stance construction, meta-annotation, corpus annotation, Brexit, Blogs
National Category
General Language Studies and Linguistics
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-79384 (URN)
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Note

TO BE PUBLISHED!!

Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-09-04
Chatzimparmpas, A., Bibi, S., Zozas, I. & Kerren, A. (2019). Analyzing the Evolution of JavaScript Applications. In: Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE: . Paper presented at 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019), May 4-5, 2019, Heraklion, Greece (pp. 359-366). SciTePress, 1
Open this publication in new window or tab >>Analyzing the Evolution of JavaScript Applications
2019 (English)In: Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, SciTePress, 2019, Vol. 1, p. 359-366Conference paper, Published paper (Refereed)
Abstract [en]

Software evolution analysis can shed light on various aspects of software development and maintenance. Up to date, there is little empirical evidence on the evolution of JavaScript (JS) applications in terms of maintainability and changeability, even though JavaScript is among the most popular scripting languages for front-end web applications. In this study, we investigate JS applications’ quality and changeability trends over time by examining the relevant Laws of Lehman. We analyzed over 7,500 releases of JS applications and reached some interesting conclusions. The results show that JS applications continuously change and grow, there are no clear signs of quality degradation while the complexity remains the same over time, despite the fact that the understandability of the code deteriorates.

Place, publisher, year, edition, pages
SciTePress, 2019
Keywords
Software Evolution, Lehman’s Laws, JavaScript, Maintenance, Software Quality
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-80639 (URN)10.5220/0007727603590366 (DOI)978-989-758-375-9 (ISBN)
Conference
14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019), May 4-5, 2019, Heraklion, Greece
Available from: 2019-02-18 Created: 2019-02-18 Last updated: 2019-08-27Bibliographically approved
Skeppstedt, M., Ahltorp, M., Kerren, A., Rzepka, R. & Araki, K. (2019). Application of a topic model visualisation tool to a second language. In: Book of Abstracts of the CLARIN Annual Conference 2019, Leipzig, Germany: . Paper presented at CLARIN Annual Conference 2019, 30 September - 2 October 2019, Leipzig, Germany.
Open this publication in new window or tab >>Application of a topic model visualisation tool to a second language
Show others...
2019 (English)In: Book of Abstracts of the CLARIN Annual Conference 2019, Leipzig, Germany, 2019Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

We explored adaptions required for applying a topic modelling tool to a language that is very different from the one for which the tool was originally developed. The tool, which enables text analysis on the output of topic modelling, was developed for English, and we here applied it on Japanese texts. As white space is not used for indicating word boundaries in Japanese, the texts had to be pre-tokenised and white space inserted to indicate a token segmentation, before the texts could be imported into the tool. The tool was also extended by the addition of word translations and phonetic readings to support users who are second-language speakers of Japanese.

Keywords
Topic Models, Visualization, Japanese, Text Mining, Visual Text Analysis
National Category
Language Technology (Computational Linguistics) Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-87108 (URN)
Conference
CLARIN Annual Conference 2019, 30 September - 2 October 2019, Leipzig, Germany
Projects
DISA-DH
Note

TO BE PUBLISHED!!!

Available from: 2019-08-07 Created: 2019-08-07 Last updated: 2019-09-18
Bechmann, D., Chessa, M., Cláudio, A.-P., Imai, F., Kerren, A., Richard, P., . . . Tremeau, A. (Eds.). (2019). Computer Vision, Imaging and Computer Graphics - Theory and Applications: International Joint Conference, VISIGRAPP 2018, Funchal-Madeira, Portugal, January 27-29, 2018, Revised Selected Papers. Springer
Open this publication in new window or tab >>Computer Vision, Imaging and Computer Graphics - Theory and Applications: International Joint Conference, VISIGRAPP 2018, Funchal-Madeira, Portugal, January 27-29, 2018, Revised Selected Papers
Show others...
2019 (English)Collection (editor) (Refereed)
Place, publisher, year, edition, pages
Springer, 2019. p. 392
Series
Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937 ; 997
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-86159 (URN)10.1007/978-3-030-26756-8 (DOI)978-3-030-26755-1 (ISBN)978-3-030-26756-8 (ISBN)
Available from: 2019-07-03 Created: 2019-07-03 Last updated: 2019-08-30Bibliographically approved
Martins, R. M. & Kerren, A. (2019). Efficient Dynamic Time Warping for Big Data Streams. In: Abe, N; Liu, H; Pu, C; Hu, X; Ahmed, N; Qiao, M; Song, Y; Kossmann, D; Liu, B; Lee, K; Tang, J; He, J; Saltz, J (Ed.), Proceedings of the IEEE International Conference on Big Data (Big Data '18): Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management. Paper presented at 3rd Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management at IEEE Big Data '18, 10-13 December, 2018, Seattle, USA (pp. 2924-2929). IEEE
Open this publication in new window or tab >>Efficient Dynamic Time Warping for Big Data Streams
2019 (English)In: Proceedings of the IEEE International Conference on Big Data (Big Data '18): Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management / [ed] Abe, N; Liu, H; Pu, C; Hu, X; Ahmed, N; Qiao, M; Song, Y; Kossmann, D; Liu, B; Lee, K; Tang, J; He, J; Saltz, J, IEEE, 2019, p. 2924-2929Conference paper, Published paper (Refereed)
Abstract [en]

Many common data analysis and machine learning algorithms for time series, such as classification, clustering, or dimensionality reduction, require a distance measurement between pairs of time series in order to determine their similarity. A variety of measures can be found in the literature, each with their own strengths and weaknesses, but the Dynamic Time Warping (DTW) distance measure has occupied an important place since its early applications for the analysis and recognition of spoken word. The main disadvantage of the DTW algorithm is, however, its quadratic time and space complexity, which limits its practical use to relatively small time series. This issue is even more problematic when dealing with streaming time series that are continuously updated, since the analysis must be re-executed regularly and with strict running time constraints. In this paper, we describe enhancements to the DTW algorithm that allow it to be used efficiently in a streaming scenario by supporting an append operation for new time steps with a linear complexity when an exact, error-free DTW is needed, and even better performance when either a Sakoe-Chiba band is used, or when a sliding window is the desired range for the data. Our experiments with one synthetic and four natural data sets have shown that it outperforms other DTW implementations and the potential errors are, in general, much lower than another state-of-the-art approximated DTW technique.

Place, publisher, year, edition, pages
IEEE, 2019
Series
IEEE International Conference on Big Data, ISSN 2639-1589
Keywords
time series, dynamic time warping, streaming
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-78735 (URN)10.1109/BigData.2018.8621878 (DOI)000468499303001 ()2-s2.0-85062589330 (Scopus ID)978-1-5386-5035-6 (ISBN)978-1-5386-5036-3 (ISBN)
Conference
3rd Workshop on Real-time & Stream Analytics in Big Data & Stream Data Management at IEEE Big Data '18, 10-13 December, 2018, Seattle, USA
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-08-29Bibliographically approved
Skeppstedt, M., Kerren, A. & Stede, M. (2019). Finding Reasons for Vaccination Hesitancy: Evaluating Semi-Automatic Coding of Internet Discussion Forums. In: Lucila Ohno-Machado and Brigitte Séroussi (Ed.), MEDINFO 2019: Health and Wellbeing e-Networks for All: Proceedings of the 17th World Congress on Medical and Health Informatics. Paper presented at 17th World Congress on Medical and Health Informatics (MEDINFO '19), 25-30 August, 2019, Lyon, France. (pp. 348-352). IOS Press
Open this publication in new window or tab >>Finding Reasons for Vaccination Hesitancy: Evaluating Semi-Automatic Coding of Internet Discussion Forums
2019 (English)In: MEDINFO 2019: Health and Wellbeing e-Networks for All: Proceedings of the 17th World Congress on Medical and Health Informatics / [ed] Lucila Ohno-Machado and Brigitte Séroussi, IOS Press, 2019, p. 348-352Conference paper, Published paper (Refereed)
Abstract [en]

Computer-assisted text coding can facilitate the analysis of large text collections. To evaluate the functionality of providing an analyst with a ranked list of suggestions for suitable text codes, we used a data set of discussion posts, which had been manually coded for reasons given for taking a stance on the topic of vaccination. We trained a logistic regression classifier to rank these reasons according to the probability that they would be present in the post. The approach was evaluated for its ability to include the expected reasons among the n top-ranked reasons, using an n between 1 and 6. The logistic regression-based ranking was more effective than the baseline, which ranked reasons according to their frequency in the training data. To provide such a list of possible codes, ranked by logistic regression, could therefore be a useful feature in a tool for text coding.

Place, publisher, year, edition, pages
IOS Press, 2019
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 264
Keywords
Vaccination Refusal, Text Mining, Supervised Machine Learning
National Category
Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-82449 (URN)10.3233/SHTI190241 (DOI)978-1-64368-003-3 (ISBN)978-1-64368-002-6 (ISBN)
Conference
17th World Congress on Medical and Health Informatics (MEDINFO '19), 25-30 August, 2019, Lyon, France.
Projects
Navigating in streams of opinions: Extracting and visualising arguments in opinionated texts
Funder
Swedish Research Council, 2016-06681
Available from: 2019-05-06 Created: 2019-05-06 Last updated: 2019-08-28
Pohl, M. & Kerren, A. (2019). Human Factors and Multilayer Networks. In: : . Paper presented at Workshop on Visualization of Multilayer Networks (MNLVIS '19) at IEEE VIS '19, October 21, 2019, Vancouver, BC, Canada.
Open this publication in new window or tab >>Human Factors and Multilayer Networks
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Analysts of specific application domains, such as experts in systems biology or social scientists, are often interested to visually analyze a number of different network structures in conjunction, for example by using various visual structures of so-called multilayer networks. From the perspective of the human analyst, a sufficient perception and, consequently, a good understanding of those visual representations of multilayer networks is a non-trivial and often challenging task. Despite this practical importance and the clearly interesting visualization challenges, only few evaluation studies exist that investigate usability and cognitive issues of complex networks or, more specifically, multilayer networks. In this position paper, we address two main goals. On the one hand, we discuss existing studies from the fields of human-computer interaction and cognitive psychology that could inform the designers of multilayer network visualization in the future. On the other hand, we formulate first tentative recommendations for the design of multilayer networks, identify open issues in this context, and clarify possible future directions of research.

Keywords
Graph Drawing, Network Visualization, Visualization, Interaction, Cognition, Human Factors, Empirical Studies, Cognitive Load
National Category
Human Computer Interaction Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-87106 (URN)
Conference
Workshop on Visualization of Multilayer Networks (MNLVIS '19) at IEEE VIS '19, October 21, 2019, Vancouver, BC, Canada
Projects
DISA-VAESS
Available from: 2019-08-07 Created: 2019-08-07 Last updated: 2019-09-16
Kerren, A., Hurter, C. & Braz, J. (Eds.). (2019). Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019, Prague, Czech Republic, February 25-27, 2019: Volume 3: IVAPP. Paper presented at International Conference on Information Visualization Theory and Applications (IVAPP '19), Prague, Czech Republic, February 25-27, 2019. SciTePress
Open this publication in new window or tab >>Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2019, Prague, Czech Republic, February 25-27, 2019: Volume 3: IVAPP
2019 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

This book contains the proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) which was organized and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC), in cooperation with ACM SIGCHI, ACM SIGGRAPH, AFIG, Eurographics and UXPA International.

The proceedings here published demonstrate new and innovative solutions and highlight technical problems in each field that are challenging and worthwhile being disseminated to the interested research audiences.

VISIGRAPP 2019 was organized to promote a discussion forum about the conference’s research topics be- tween researchers, developers, manufacturers and end-users, and to establish guidelines in the development of more advanced solutions.

We received a high number of paper submissions for this edition of VISIGRAPP, 396 in total, with contribu- tions from all five continents. This attests to the success and global dimension of VISIGRAPP. To evaluate each submission, we used a double-blind evaluation method where each paper was reviewed by two to six experts from the International Program Committee (IPC).

The IPC selected for oral presentation and for publication as full papers 12 papers from GRAPP, 6 for HUCAPP, 12 papers for IVAPP, and 36 papers for VISAPP, which led to a result for the full-paper accep- tance ratio of 17% and a high-quality program. Apart from the above full papers, the conference program also features 88 short papers and 115 poster presentations. We hope that these conference proceedings, which are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index, SCOPUS, DBLP, Semantic Scholar, Google Scholar and EI, will help the Computer Vision, Imaging, Visualization and Computer Graphics communities to find interesting research work. Moreover, we are proud to inform that the program also includes four plenary keynote lectures, given by internationally distinguished researchers, namely Daniel McDuff (Microsoft, United States), Diego Gutierrez (Universidad de Zaragoza, Spain), Jiri Matas (Czech Technical University in Prague, Faculty of Electrical Engineering, Czech Republic) and Dima Damen (University of Bristol, United Kingdom), thus contributing to increase the overall quality of the con- ference and to provide a deeper understanding of the conference’s interest fields.

Furthermore, a short list of the presented papers will be selected to be expanded into a forthcoming book of VISIGRAPP Selected Papers to be published by Springer during 2019 in the CCIS series. Also, a short list of presented papers will be selected for publication of extended and revised versions in a special issue of the Open Access Information Science Journal (IVAPP) and in a special issue of the Pattern Recognition and Artificial Intelligence Journal (VISAPP). All papers presented at this conference will be available at the SCITEPRESS Digital Library. Three awards are delivered at the closing session, to recognize the best conference paper, the best student paper and the best poster for each of the four conferences.

We would like to express our thanks, first of all, to the authors of the technical papers, whose work and dedication made possible to put together a program that we believe to be very exciting and of high technical quality. Next, we would like to thank the Area Chairs, all the members of the program committee and auxiliary reviewers, who helped us with their expertise and time. We would also like to thank the invited speakers for their invaluable contribution and for sharing their vision in their talks. Special thanks should be addressed to the INSTICC Steering Committee whose invaluable work made this event possible.

We wish you all an exciting conference and an unforgettable stay in Prague, Czech Republic. We hope to meet you again for the next edition of VISIGRAPP, details of which are available at http://www.visigrapp.org.

Place, publisher, year, edition, pages
SciTePress, 2019. p. 355
Keywords
Information Visualization
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-81078 (URN)978-989-758-354-4 (ISBN)
Conference
International Conference on Information Visualization Theory and Applications (IVAPP '19), Prague, Czech Republic, February 25-27, 2019
Available from: 2019-03-14 Created: 2019-03-14 Last updated: 2019-03-21Bibliographically approved
Kucher, K. & Kerren, A. (2019). Text Visualization Revisited: The State of the Field in 2019. In: TBA (Ed.), EuroVis 2019 - Posters: . Paper presented at The 21th EG/VGTC Conference on Visualization (EuroVis '19), Porto, Portugal, 3-7 June, 2019. Eurographics - European Association for Computer Graphics
Open this publication in new window or tab >>Text Visualization Revisited: The State of the Field in 2019
2019 (English)In: EuroVis 2019 - Posters / [ed] TBA, Eurographics - European Association for Computer Graphics, 2019Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Text and document data visualization is an important research field within information visualization and visual analytics with multiple application domains including digital humanities and social media, for instance. During the past five years, we have been collecting text visualization techniques described in peer-reviewed literature, categorizing them according to a detailed categorization schema, and providing the resulting manually curated collection in an online survey browser. In this poster paper, we present the updated results of analyses of this data set as of spring 2019. Compared to the recent surveys and meta-analyses that mainly focus on particular aspects and problems related to text visualization, our results provide an overview of the current state of the text visualization field and the respective research community in general.

Place, publisher, year, edition, pages
Eurographics - European Association for Computer Graphics, 2019
Keywords
visual analytics, visualization, information visualization, text visualization
National Category
Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-82464 (URN)
Conference
The 21th EG/VGTC Conference on Visualization (EuroVis '19), Porto, Portugal, 3-7 June, 2019
Note

TO BE PUBLISHED!!!

Available from: 2019-05-07 Created: 2019-05-07 Last updated: 2019-05-08
Skeppstedt, M., Rzepka, R., Kerren, A. & Araki, K. (2019). Visualising and Evaluating the Effects of Combining Active Learning with Word Embedding Features. In: : . Paper presented at 15th Conference on Natural Language Processing (KONVENS '19), October 9-11, 2019, Erlangen-Nürnberg, Germany. German Society for Computational Linguistics and Language Technology (GSCL)
Open this publication in new window or tab >>Visualising and Evaluating the Effects of Combining Active Learning with Word Embedding Features
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

A tool that enables the use of active learning, as well as the incorporation of word embeddings, was evaluated for its ability to decrease the training data set size required for a named entity recognition model. Uncertainty-based active learning and the use of word embeddings led to very large performance improvements on small data sets for the entity categories PERSON and LOCATION. In contrast, the embedding features used were shown to be unsuitable for detecting entities belonging to the ORGANISATION category. The tool was also extended with functionality for visualising the usefulness of the active learning process and of the word embeddings used. The visualisations provided were able to indicate the performance differences between the entities, as well as differences with regards to usefulness of the embedding features.

Place, publisher, year, edition, pages
German Society for Computational Linguistics and Language Technology (GSCL), 2019
Keywords
Visualization, active learning, word embedding
National Category
Language Technology (Computational Linguistics) Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-89000 (URN)
Conference
15th Conference on Natural Language Processing (KONVENS '19), October 9-11, 2019, Erlangen-Nürnberg, Germany
Projects
Navigating in streams of opinions
Funder
Swedish Research Council, 2016-06681Swedish Research Council, 2017-00626
Note

TO BE PUBLISHED!

Available from: 2019-09-06 Created: 2019-09-06 Last updated: 2019-09-18
Projects
Advances in the description and explanation of stance in discourse using visual and computational text analytics - StaViCTA [2012-05659_VR]; Linnaeus University; Publications
Simaki, V., Paradis, C. & Kerren, A. (2019). A two-step procedure to identify stance constructions in discourse from political blogs. Corpora, 14(3)Simaki, V., Panagiotis, S., Paradis, C. & Kerren, A. (2018). Detection of Stance-Related Characteristics in Social Media Text. In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence (SETN '18): . Paper presented at The 10th Hellenic Conference on Artificial Intelligence (SETN '18), 9-15 July 2018, Patras, Greece. ACM Publications, Article ID 38.
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0519-2537

Search in DiVA

Show all publications