Recent Advances in Bibliometric-Enhanced Information Retrieval

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panel paper presented at ASIST 2016 in Copenhagen

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Measuring the usefulness of Knowledge Organization Systems in Information Ret...

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The objective of the OSCOSS research project on "Opening Scholarly Communication in the Social Sciences" is to build a coherent collaboration environment that facilitates scholarly communication workflows of social scientists in the roles of authors, reviewers, editors and readers. This paper presents the implementation of the core of this environment: the integration of the Fidus Writer academic word processor with the Open Journal Systems (OJS) submission and review management system.

Opening Scholarly Communication in Social Sciences by Connecting Collaborativ...

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Les médias sociaux et leur introduction dans un contexte académique ont généré de nouvelles opportunités pour les chercheurs de diffuser leur recherche plus rapidement et à une audience plus grande. Twitter, Facebook, ainsi que les plateformes spécialisées comme ResearchGate et Academia.edu, offrent plusieurs possibilités aux chercheurs d’augmenter leur visibilité et celle de leur recherche. Ces plateformes constituent aussi certains défis pour les chercheurs : leur multiplication fait en sorte qu’ils peuvent s’y perdre et entraîner des pertes de temps. Dans certains cas extrêmes, des commentaires inappropriés émis par les chercheurs sur les médias sociaux ont même mené à des licenciements. Dans un contexte où l’évaluation de la recherche prend une place de plus en plus importante, les activités associées aux contenus savants partagés sur les médias sociaux ont été proposées par certains comme étant des indicateurs de l’impact de ces contenus. Ces indicateurs, appelés «altmetrics» incluent, par exemple, le nombre de tweets, de liens Facebook, de lecteurs sur Mendeley, de mentions dans les blogs, d’évaluations d’experts sur F1000, de vues sur figshare ainsi que de nombreux autres événements en ligne qui se réfèrent aux documents ou acteurs scientifiques. L’idée derrière les altmetrics était de rendre l’évaluation de la recherche plus englobante, d’aller au-delà du nombre de publications et de citations, afin de capturer l’impact social sur le grand public. Ce lien entre médias sociaux et impact social demeure toutefois à prouver. Cette formation fournira un aperçu des résultats de recherche récents sur les altmetrics et donnera quelques conseils sur l’utilisation professionnelle des médias sociaux dans un contexte académique.

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Bibliometric-enhanced Retrieval Models for Big Scholarly Information Systems

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Our system will initially provide readers, authors and reviewers with an alternative, thus having the potential to gain wider acceptance and gradually replace the old, incoherent publication process of our journals and of others in related fields. It will make journals more “open” (in terms of reusability) that are open access already, and it has the potential to serve as an incentive for turning “closed” journals into open access ones. OSCOSS is funded by the DFG in the Open Access Transformation programme.

Opening Scholarly Communication in Social Sciences (OSCOSS)

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We propose an online access panel to support the evaluation process of Interactive Information Retrieval (IIR) systems. By maintaining an online access panel with users of IIR systems we assume that the recurring effort to recruit participants for web-based as well as for lab studies can be minimized. We target on using the online access panel not only for our own development processes but to open it for other interested researchers in the field of IIR. In this paper we present the concept of the online access panel as well as first implementation details.

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As more and more people use social media to communicate their view and perception of elections, researchers have increasingly been collecting and analyzing data from social media platforms. Our research focuses on social media communication related to the 2013 election of the German parlia-ment [translation: Bundestagswahl 2013]. We constructed several social media datasets using data from Facebook and Twitter. First, we identified the most relevant candidates (n=2,346) and checked whether they maintained social media accounts. The Facebook data was collected in November 2013 for the period of January 2009 to October 2013. On Facebook we identified 1,408 Facebook walls containing approximately 469,000 posts. Twitter data was collected between June and December 2013 finishing with the constitution of the government. On Twitter we identified 1,009 candidates and 76 other agents, for example, journalists. We estimated the number of relevant tweets to exceed eight million for the period from July 27 to September 27 alone. In this document we summarize past research in the literature, discuss possibilities for research with our data set, explain the data collection procedures, and provide a description of the data and a discussion of issues for archiving and dissemination of social media data.

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In this paper we describe a case study where researchers in the social sciences (n=19) assess topical relevance for controlled search terms, journal names and author names which have been compiled automatically by bibliometric-enhanced information retrieval (IR) services. We call these bibliometric-enhanced IR services Search Term Recommender (STR), Journal Name Recommender (JNR) and Author Name Recommender (ANR) in this paper. The researchers in our study (practitioners, PhD students and postdocs) were asked to assess the top n pre-processed recommendations from each recommender for specific research topics which have been named by them in an interview before the experiment. Our results show clearly that the presented search term, journal name and author name recommendations are highly relevant to the researchers’ topic and can easily be integrated for search in Digital Libraries. The average precision for top ranked recommendations is 0.75 for author names, 0.74 for search terms and 0.73 for journal names. The relevance distribution differs largely across topics and researcher types. Practitioners seem to favor author name recommendations while postdocs have rated author name recommendations the lowest. In the experiment the small postdoc group (n=3) favor journal name recommendations.

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With the increasing size of digital libraries (DLs) it has become a challenge to identify author names correctly and assign publications to them. The situation becomes more critical when different persons share the same name (homonym problem) or when the names of authors are presented in several different ways (synonym problem). This paper focuses on homonym names in the computer science bibliography DBLP. The goal of this study is to implement and evaluate a method which uses co-authorship networks in order to disambiguate homonym names, especially common names. The results show that the implemented method has a good performance and can be used for author name disambiguation of sparse bibliographic records.

Using co-authorship networks for author name disambiguation

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Destaque (20)

Measuring the usefulness of Knowledge Organization Systems in Information Ret...

Opening Scholarly Communication in Social Sciences by Connecting Collaborativ...

Lés médias sociaux dans la communication et l'évaluation scientifique : résul...

Haustein, S. (2017). The evolution of scholarly communication and the reward ...

Bibliometric-enhanced Retrieval Models for Big Scholarly Information Systems

Demonstrating a Framework for KOS-based Recommendations Systems

Opening Scholarly Communication in Social Sciences (OSCOSS)

Introduction of the 3rd International Workshop on Bibliometric-enhanced Infor...

Establishing an Online Access Panel for Interactive Information Retrieval Res...

PEP-TF: Social Media Monitoring of the Campaigns for the 2013 German Bundesta...

Past, present and future of scientific information

Recent applications of Knowledge Organization Systems

Opening Scholarly Communication in the Social Sciences

Introduction to the 15th NKOS workshop @TPDL2016

Are topic-specific search term, journal name and author name recommendations ...

Analyzing the research output presented at European Networked Knowledge Organ...

Pennants for Descriptors

Introduction of the Bibliometric-enhanced Information Retrieval (BIR) workshop

Assessing a human mediated current awareness service

Using co-authorship networks for author name disambiguation

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From closed to open access: A case study of flipped journals

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4th Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural...

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Contextualisation has proven to be effective in tailoring search results towards the users’ information need. While this is true for a basic query search, the usage of contextual session information during exploratory search especially on the level of browsing has so far been underexposed in research. In this paper, we present two approaches that contextualise browsing on the level of structured metadata in a Digital Library (DL), (1) one variant bases on document similarity and (2) one variant utilises implicit session information, such as queries and different document metadata encountered during the session of a users. We evaluate our approaches in a living lab environment using a DL in the social sciences and compare our contextualisation approaches against a non-contextualised approach. For a period of more than three months we analysed 47,444 unique retrieval sessions that contain search activities on the level of browsing. Our results show that a contextualisation of browsing significantly outperforms our baseline in terms of the position of the first clicked item in the result set. The mean rank of the first clicked document (measured as mean first relevant - MFR) was 4.52 using a non-contextualised ranking compared to 3.04 when re-ranking the result lists based on similarity to the previously viewed document. Furthermore, we observed that both contextual approaches show a noticeably higher clickthrough rate. A contextualisation based on document similarity leads to almost twice as many document views compared to the non-contextualised ranking.

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Industrie 4.0

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From closed to open access: A case study of flipped journals

Highly cited references in PLOS ONE and their in-text usage over time

4th Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural...

Bibliometric-enhanced Information Retrieval: Connecting IR with Bibliometrics

Analyzing the network structure and gender differences of the “NKOS community”

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Bedeutung von Text Mining am Beispiel der Sozialwissenschaften

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41st European Conference on Information Retrieval (ECIR 2019)

Offenes kollaboratives Schreiben: Eine „Open Science“-Infrastruktur am Beispi...

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