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Kerren, Andreas, Dr.-Ing.ORCID iD iconorcid.org/0000-0002-0519-2537
Publications (10 of 141) Show all publications
Kucher, K., Martins, R. M. & Kerren, A. (2018). Analysis of VINCI 2009–2017 Proceedings. In: Karsten Klein, Yi-Na Li, and Andreas Kerren (Ed.), Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden: . Paper presented at 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden (pp. 97-101). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Analysis of VINCI 2009–2017 Proceedings
2018 (English)In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 97-101Conference paper, Published paper (Refereed)
Abstract [en]

Both the metadata and the textual contents of scientific publications can provide us with insights about the development and the current state of the corresponding scientific community. In this short paper, we take a look at the proceedings of VINCI from the previous years and conduct several types of analyses. We summarize the yearly statistics about different types of publications, identify the overall authorship statistics and the most prominent contributors, and analyze the current community structure with a co-authorship network. We also apply topic modeling to identify the most prominent topics discussed in the publications. We hope that the results of our work will provide insights for the visualization community and will also be used as an overview for researchers previously unfamiliar with VINCI.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018
Keywords
meta-analysis, survey, overview, visualization, scientific literature, topic modeling
National Category
Computer Sciences Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-75857 (URN)10.1145/3231622.3231641 (DOI)978-1-4503-6501-7 (ISBN)
Conference
11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden
Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-09-11Bibliographically approved
Kucher, K., Skeppstedt, M. & Kerren, A. (2018). Application of Interactive Computer-Assisted Argument Extraction to Opinionated Social Media Texts. In: Karsten Klein, Yi-Na Li, and Andreas Kerren (Ed.), Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18): . Paper presented at 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden (pp. 102-103). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Application of Interactive Computer-Assisted Argument Extraction to Opinionated Social Media Texts
2018 (English)In: Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18) / [ed] Karsten Klein, Yi-Na Li, and Andreas Kerren, Association for Computing Machinery (ACM), 2018, p. 102-103Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The analysis of various opinions and arguments in textual data can be facilitated by automatic topic modeling methods; however, the exploration and interpretation of the resulting topics and terms may prove to be difficult to the analysts. Opinions, stances, arguments, topics, terms, and text documents are usually connected with many-to-many relationships for such tasks. Exploratory visual analysis with interactive tools can help the analysts to get an overview of the topics and opinions, identify particularly interesting documents, and describe main themes of various arguments. In our previous work, we introduced an interactive tool called Topics2Themes that was used for topic and theme analysis of vaccination-related discussion texts with a limited set of stance categories. In this poster paper, we describe an application of Topics2Themes to a different genre of data, namely, political comments from Reddit, and multiple sentiment and stance categories detected with automatic classifiers.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018
Keywords
visualization, interaction, topic modeling, argument extraction, text visualization, sentiment analysis, sentiment visualization, stance analysis, stance visualization, annotation
National Category
Computer Sciences Language Technology (Computational Linguistics) Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-75856 (URN)10.1145/3231622.3232505 (DOI)978-1-4503-6501-7 (ISBN)
Conference
11th International Symposium on Visual Information Communication and Interaction (VINCI '18), 13-15 August 2018, Växjö, Sweden
Funder
Swedish Research Council, 2016-06681
Available from: 2018-06-13 Created: 2018-06-13 Last updated: 2018-09-11Bibliographically approved
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.
Open this publication in new window or tab >>Detection of Stance-Related Characteristics in Social Media Text
2018 (English)In: Proceedings of the 10th Hellenic Conference on Artificial Intelligence (SETN '18), ACM Publications, 2018, article id 38Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a study for the identification of stance-related features in text data from social media. Based on our previous work on stance and our findings on stance patterns, we detected stance-related characteristics in a data set from Twitter and Facebook. We extracted various corpus-, quantitative- and computational-based features that proved to be significant for six stance categories (contrariety, hypotheticality, necessity, prediction, source of knowledge, and uncertainty), and we tested them in our data set. The results of a preliminary clustering method are presented and discussed as a starting point for future contributions in the field. The results of our experiments showed a strong correlation between different characteristics and stance constructions, which can lead us to a methodology for automatic stance annotation of these data.

Place, publisher, year, edition, pages
ACM Publications, 2018
Keywords
stance-taking, text clustering, feature extraction, social media text
National Category
Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-71735 (URN)10.1145/3200947.3201017 (DOI)978-1-4503-6433-1 (ISBN)
Conference
The 10th Hellenic Conference on Artificial Intelligence (SETN '18), 9-15 July 2018, Patras, Greece
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2018-03-22 Created: 2018-03-22 Last updated: 2018-09-10Bibliographically approved
Kucher, K., Paradis, C. & Kerren, A. (2018). DoSVis: Document Stance Visualization. In: Alexandru C. Telea, Andreas Kerren, and José Braz (Ed.), Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '18): . Paper presented at International Conference on Information Visualization Theory and Applications (IVAPP), Funchal-Madeira, Portugal, 27-29 January, 2018 (pp. 168-175). SciTePress, 3
Open this publication in new window or tab >>DoSVis: Document Stance Visualization
2018 (English)In: Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '18) / [ed] Alexandru C. Telea, Andreas Kerren, and José Braz, SciTePress, 2018, Vol. 3, p. 168-175Conference paper, Published paper (Refereed)
Abstract [en]

Text visualization techniques often make use of automatic text classification methods. One of such methods is stance analysis, which is concerned with detecting various aspects of the writer’s attitude towards utterances expressed in the text. Existing text visualization approaches for stance classification results are usually adapted to textual data consisting of individual utterances or short messages, and they are often designed for social media or debate monitoring tasks. In this paper, we propose a visualization approach called DoSVis (Document Stance Visualization) that focuses instead on individual text documents of a larger length. DoSVis provides an overview of multiple stance categories detected by our classifier at the utterance level as well as a detailed text view annotated with classification results, thus supporting both distant and close reading tasks. We describe our approach by discussing several application scenarios involving business reports and works of literature. 

Place, publisher, year, edition, pages
SciTePress, 2018
Keywords
Stance Visualization, Sentiment Visualization, Text Visualization, Stance Analysis, Sentiment Analysis, Text Analytics, Information Visualization, Interaction
National Category
Computer Sciences Human Computer Interaction Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-68428 (URN)10.5220/0006539101680175 (DOI)978-989-758-289-9 (ISBN)
Conference
International Conference on Information Visualization Theory and Applications (IVAPP), Funchal-Madeira, Portugal, 27-29 January, 2018
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2018-04-12Bibliographically approved
Simaki, V., Paradis, C. & Kerren, A. (2018). Evaluating stance-annotated sentences from the Brexit Blog Corpus: A quantitative linguistic analysis. ICAME Journal/International Computer Archive of Modern English, 42(1), 133-166
Open this publication in new window or tab >>Evaluating stance-annotated sentences from the Brexit Blog Corpus: A quantitative linguistic analysis
2018 (English)In: ICAME Journal/International Computer Archive of Modern English, ISSN 0801-5775, E-ISSN 1502-5462, Vol. 42, no 1, p. 133-166Article in journal (Refereed) Published
Abstract [en]

This paper offers a formally driven quantitative analysis of stance-annotated sentences in the Brexit Blog Corpus (BBC). Our goal is to highlight linguistic features that determine the formal profiles of six stance categories (contrariety, hypotheticality, necessity, prediction, source of knowledge and uncertainty) in a subset of the BBC. The study has two parts: firstly, it examines a large number of formal linguistic features that occur in the sentences in order to describe the specific characteristics of each category, and secondly, it compares characteristics in the entire data set in order to determine linguistic similarities throughout the data set. We show that among the six stance categories in the corpus, contrariety and necessity are the most discriminative ones, with the former using longer sentences, more conjunctions, more repetitions and shorter forms than the sentences expressing other stances. The latter has longer lexical forms but shorter sentences, which are syntactically more complex. We show that stance in our data set is expressed in sentences with around 21 words per sentence. The sentences consist mainly of alphabetical characters forming a varied vocabulary without special forms, such as digits or special characters.

Place, publisher, year, edition, pages
De Gruyter Open, 2018
Keywords
stance-taking, corpus annotation, political blog text, statistical analysis, formal features
National Category
Language Technology (Computational Linguistics) Specific Languages
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-70768 (URN)10.1515/icame-2018-0007 (DOI)
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2018-02-12 Created: 2018-02-12 Last updated: 2018-04-19
Kerren, A., Klein, K. & Li, Y.-N. (Eds.). (2018). Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18): Växjö, Sweden, August 13-15, 2018. Paper presented at The 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), Växjö, Sweden, August 13-15, 2018. Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18): Växjö, Sweden, August 13-15, 2018
2018 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

Welcome to the 11th International Symposium on Visual Information Communication and Interaction (VINCI 2018) held in Växjö, Sweden from August 13th to 15th, 2018. The objective of this symposium series is to provide a forum for researchers, artists, designers and industrial practitioners to discuss the state of the art in visual communication theories, designs and applications. As in past years, the papers in these proceedings represent the most interesting and exciting recent research in the area of visual communication.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018. p. 135
Keywords
information visualization, visual analytics, visual communication, interaction, human-computer interaction, computational aesthetics
National Category
Information Systems
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-77314 (URN)10.1145/3231622 (DOI)978-1-4503-6501-7 (ISBN)
Conference
The 11th International Symposium on Visual Information Communication and Interaction (VINCI '18), Växjö, Sweden, August 13-15, 2018
Available from: 2018-08-23 Created: 2018-08-23 Last updated: 2018-09-10Bibliographically approved
Telea, A. C., Kerren, A. & Braz, J. (Eds.). (2018). Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018, Funchal, Madeira - Portugal, January 27-29, 2018: Volume 3. Paper presented at International Conference on Information Visualization Theory and Applications (IVAPP '18), Funchal, Madeira - Portugal, January 27-29, 2018. SciTePress
Open this publication in new window or tab >>Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2018, Funchal, Madeira - Portugal, January 27-29, 2018: Volume 3
2018 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

This book contains the proceedings of the 13th International Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) which was organized and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC), in cooperation with AFIG and Eurographics. 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 2018 was organized to promote a discussion forum about the conference’s research topics between 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, 321 in total, with contributions 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 14 papers from GRAPP, 6 for HUCAPP, 12 papers for IVAPP, and 40 papers for VISAPP, which led to a result for the full-paper acceptance ratio of 22% and a high-quality program. Apart from the above full papers, the conference program also features 83 short papers and 68 poster presentations. We hope that these conference proceedings, which are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index, INSPEC, DBLP, 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 Carol O'Sullivan (Trinity College Dublin, Ireland), Alexander Bronstein (Israel Institute of Technology,Tel Aviv University and Intel Corporation, Israel), Falk Schreiber (University of Konstanz, Germany and Monash University Melbourne, Australia) and Catherine Pelachaud (CNRS/University of Pierre and Marie Curie, France), thus contributing to increase the overall quality of the conference 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 2018 in the CCIS series. All papers presented at this conference will be available at the SCITEPRESS Digital Library. Two awards are delivered at the closing session, to recognize the best conference paper and the best student paper for each of the four tracks. The meeting is complemented with the Special Session on Visual Computing in Engineering Applications (VCEA) and two tutorials entitled “Visual Intelligence in Egocentric (First-Person) Vision Systems” and “Understanding Human Motion Primitives”. 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 Funchal, Madeira, Portugal. 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, 2018. p. 365
Keywords
Information Visualization
National Category
Computer Sciences
Research subject
Computer and Information Sciences Computer Science, Computer Science; Computer Science, Information and software visualization; Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-69833 (URN)978-989-758-289-9 (ISBN)
Conference
International Conference on Information Visualization Theory and Applications (IVAPP '18), Funchal, Madeira - Portugal, January 27-29, 2018
Available from: 2018-01-14 Created: 2018-01-14 Last updated: 2018-04-12Bibliographically approved
Skeppstedt, M., Stede, M. & Kerren, A. (2018). Stance-taking in topics extracted from vaccine-related tweets and discussion forum posts. In: : . Paper presented at 3rd Workshop on Workshop on Social Media Mining for Health Applications (SMM4H '18) at EMNLP '18, 31 Oct - 1 Nov, 2018, Brussels, Belgium. Association for Computational Linguistics
Open this publication in new window or tab >>Stance-taking in topics extracted from vaccine-related tweets and discussion forum posts
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The occurrence of stance-taking towards vaccination was measured in documents extracted by topic modelling from two different corpora, one discussion forum corpus and one tweet corpus. For some of the topics extracted, their most closely associated documents  contained a proportion of vaccine stance-taking texts that exceeded the corpus average by a large margin. These extracted document sets would, therefore, form a useful resource in a process for computer-assisted analysis of argumentation on the subject of vaccination. 

Place, publisher, year, edition, pages
Association for Computational Linguistics, 2018
Keywords
text analysis, topic modelling, stance
National Category
Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization; Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-77344 (URN)
Conference
3rd Workshop on Workshop on Social Media Mining for Health Applications (SMM4H '18) at EMNLP '18, 31 Oct - 1 Nov, 2018, Brussels, Belgium
Funder
Swedish Research Council, 2016-06681
Note

TO BE PUBLISHED!

Available from: 2018-08-27 Created: 2018-08-27 Last updated: 2018-09-10
Kucher, K., Paradis, C. & Kerren, A. (2018). The State of the Art in Sentiment Visualization. Computer graphics forum (Print), 37(1), 71-96, Article ID CGF13217.
Open this publication in new window or tab >>The State of the Art in Sentiment Visualization
2018 (English)In: Computer graphics forum (Print), ISSN 0167-7055, E-ISSN 1467-8659, Vol. 37, no 1, p. 71-96, article id CGF13217Article in journal (Refereed) Published
Abstract [en]

Visualization of sentiments and opinions extracted from or annotated in texts has become a prominent topic of research over the last decade. From basic pie and bar charts used to illustrate customer reviews to extensive visual analytics systems involving novel representations, sentiment visualization techniques have evolved to deal with complex multidimensional data sets, including temporal, relational, and geospatial aspects. This contribution presents a survey of sentiment visualization techniques based on a detailed categorization. We describe the background of sentiment analysis, introduce a categorization for sentiment visualization techniques that includes 7 groups with 35 categories in total, and discuss 132 techniques from peer-reviewed publications together with an interactive web-based survey browser. Finally, we discuss insights and opportunities for further research in sentiment visualization. We expect this survey to be useful for visualization researchers whose interests include sentiment or other aspects of text data as well as researchers and practitioners from other disciplines in search of efficient visualization techniques applicable to their tasks and data. 

Place, publisher, year, edition, pages
John Wiley & Sons, 2018
Keywords
sentiment visualization, text visualization, sentiment analysis, opinion mining
National Category
Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-62644 (URN)10.1111/cgf.13217 (DOI)000426151300007 ()
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2017-04-27 Created: 2017-04-27 Last updated: 2018-03-16Bibliographically approved
Skeppstedt, M., Kucher, K., Stede, M. & Kerren, A. (2018). Topics2Themes: Computer-Assisted Argument Extraction by Visual Analysis of Important Topics. In: Mennatallah El-Assady, Annette Hautli-Janisz, and Verena Lyding (Ed.), Proceedings of the LREC 2018 Workshop “The 3rd Workshop on Visualization as Added Value in the Development, Use and Evaluation of Language Resources (VisLR III)”: . Paper presented at 3rd Workshop on Visualization as Added Value in the Development, Use and Evaluation of Language Resources (VisLR III) at LREC '18, 12 May, 2018, Miyazaki, Japan (pp. 9-16). Paris, France: European Language Resources Association (ELRA)
Open this publication in new window or tab >>Topics2Themes: Computer-Assisted Argument Extraction by Visual Analysis of Important Topics
2018 (English)In: Proceedings of the LREC 2018 Workshop “The 3rd Workshop on Visualization as Added Value in the Development, Use and Evaluation of Language Resources (VisLR III)” / [ed] Mennatallah El-Assady, Annette Hautli-Janisz, and Verena Lyding, Paris, France: European Language Resources Association (ELRA) , 2018, p. 9-16Conference paper, Published paper (Refereed)
Abstract [en]

The large collections of opinionated text that are continuously being created online, e.g., in the form of forum posts or tweets, contain arguments that might help us to better understand why opinions are held. While the task of manually extracting arguments from these large collections is an intractable one, a tool for computer-assisted extraction can (i) automatically select a subset of the text collection that contains re-occurring arguments to minimise the amount of text that the human coder has to read, and (ii) present the selected texts in a way that facilitates manual coding of arguments. We propose a tool called Topics2Themes that uses topic modelling to automatically extract important topics as well as the terms and texts most closely associated with each topic. We also provide a graphical user interface for manual argument coding, in which the user can search for arguments in the texts selected, create a theme for each type of argument detected and connect it to the texts in which it is found. Topics, terms, texts and themes are displayed as elements in four separate lists, and associations between the elements are visualised through connecting links. It is also possible to focus on one particular element through the sorting functionality provided, e.g., when a topic is selected, the terms, texts and themes associated with this topic are sorted as the top-ranked elements in their respective lists. The text collection can thereby be explored from different angles, which can be used to facilitate the argument coding and gain an overview and understanding of the arguments found in the texts. 

Place, publisher, year, edition, pages
Paris, France: European Language Resources Association (ELRA), 2018
Keywords
argument extraction, topic modelling, text analysis, argument visualization, stance visualization, text visualization, information visualization, interaction
National Category
Language Technology (Computational Linguistics) Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-70911 (URN)979-10-95546-13-9 (ISBN)
Conference
3rd Workshop on Visualization as Added Value in the Development, Use and Evaluation of Language Resources (VisLR III) at LREC '18, 12 May, 2018, Miyazaki, Japan
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659Swedish Research Council, 2016-06681
Available from: 2018-02-14 Created: 2018-02-14 Last updated: 2018-05-24
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-0519-2537

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