@inbook{293, abstract = {{Opinion mining from physician rating websites depends on the quality of the extracted information. Sometimes reviews are user-error prone and the assigned stars or grades contradict the associated content. We therefore aim at detecting random individual error within reviews. Such errors comprise the disagreement in polarity of review texts and the respective ratings. The challenges that thereby arise are (1) the content and sentiment analysis of the review texts and (2) the removal of the random individual errors contained therein. To solve these tasks, we assign polarities to automatically recognized opinion phrases in reviews and then check for divergence in rating and text polarity. The novelty of our approach is that we improve user-generated data quality by excluding error-prone reviews on German physician websites from average ratings.}}, author = {{Geierhos, Michaela and Bäumer, Frederik Simon and Schulze, Sabine and Stuß, Valentina}}, booktitle = {{Proceedings of the 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2015)}}, editor = {{Ali, Moonis and Kwon, Young Sig and Lee, Chang-Hwan and Kim, Juntae and Kim, Yongdai }}, isbn = {{978-3-319-19065-5}}, location = {{Seoul, South Korea}}, pages = {{305--315}}, publisher = {{Springer}}, title = {{{Filtering Reviews by Random Individual Error}}}, doi = {{10.1007/978-3-319-19066-2_30}}, volume = {{9101}}, year = {{2015}}, } @inproceedings{1141, author = {{Stuß, Valentina and Geierhos, Michaela}}, booktitle = {{DHd 2015: Book of Abstracts}}, location = {{Graz, Austria}}, pages = {{239--243}}, publisher = {{ZIM-ACDH}}, title = {{{Identifikation kognitiver Effekte in Online-Bewertungen}}}, year = {{2015}}, } @inproceedings{1142, author = {{Geierhos, Michaela and Bäumer, Frederik Simon}}, booktitle = {{DHd 2015: Book of Abstracts}}, location = {{Graz, Austria}}, pages = {{69--72}}, publisher = {{ZIM-ACDH}}, title = {{{Erfahrungsberichte aus zweiter Hand: Erkenntnisse über die Autorschaft von Arztbewertungen in Online-Portalen}}}, year = {{2015}}, } @article{1143, abstract = {{Der Erfahrungsaustausch zwischen Patienten findet heutzutage zunehmend im Internet statt. Bewertungsportale wie jameda, DocInsider oder imedo.de bieten Patienten und deren Angehörigen die Möglichkeit, anonym Beschwerden zu äußern oder Weiterempfehlungen auszusprechen. Gleichzeitig ermöglichen diese hunderttausend Individualerfahrungen die Erhebung der Patientenzufriedenheit sowie die Überprüfung bestehender Gerüchte, wie z. B. dass Privatpatienten schneller einen Arzttermin bekommen und weniger Zeit im Wartezimmer verbringen. Die Analyse anonymer Online-Arztbewertungen kann nur dann erfolgreich sein, wenn bei der Interpretation der Patientenerfahrungsberichte berücksichtigt wird, dass behandlungsqualitätsunabhängige Faktoren Auswirkungen auf die subjektive Bewertung und das Beschwerdeverhalten haben. Ein neuer Ansatz ist daher, bedeutende Indikatoren für die Patientenzufriedenheit im Web 2.0 zur Generierung eines detaillierten Erfahrungs- und Patientenstimmungsbildes unter Berücksichtigung demographischer und regionaler Einflüsse zu ermitteln.}}, author = {{Geierhos, Michaela and Schulze, Sabine}}, journal = {{ForschungsForum Paderborn}}, pages = {{14--19}}, publisher = {{Universität Paderbon}}, title = {{{Der zufriedene Patient 2.0: Analyse anonymer Arztbewertungen zur Generierung eines Patientenstimmungsbildes}}}, volume = {{18}}, year = {{2015}}, } @inproceedings{1144, abstract = {{Adopting the concept of “Local Grammars” (M. Gross), which were successfully applied in practice by (Geierhos, 2010) to biographical information extraction in English our project aims to detect, encode, and finally visualize relations between persons. Our corpus consists of the digitised biographical lexicon “Neue Deutsche Biographie (NDB)”, roughly 21.000 biographies in 25 volumes in print since 1953. We developed local grammars and suitable dictionaries to describe interpersonal relations and applied them to the corpus with Unitex 3.1. The local grammars were designed to integrate existing TEI-XML structures in the corpus. Using the ability of local grammars in Unitex to act as transducers we were able to produce XML-Tags and encode semantic information. Based on grammars for personal names and places we described interpersonal relations like to study, predecessors and successors as well as friends and circles. Afterwards we identified persons (as given in the authority file or index). Finally we displayed relations on our website in an interactive and dynamic way. Utilizing the Javascript library D3.js we represented named relations between identified individuals as ego centred network graphs.}}, author = {{Stotz, Sophia and Stuß, Valentina and Reinert , Matthias and Schrott, Maximilian}}, booktitle = {{Proceedings of the First Conference on Biographical Data in a Digital World 2015}}, editor = {{ter Braake, Serge and Fokkens, Antske and Sluijter, Ronald and Declerck, Thierry and Wandl-Vogt, Eveline}}, issn = {{16130073}}, keywords = {{Local Grammar, Relation Extraction, Visualisation}}, location = {{Amsterdam, Netherlands}}, pages = {{74--80}}, publisher = {{CEUR-WS.org}}, title = {{{Interpersonal relations in biographical dictionaries. A case study}}}, volume = {{1399}}, year = {{2015}}, } @inproceedings{1145, abstract = {{Received medical services are increasingly discussed and recommended on physician rating websites (PRWs). The reviews and ratings on these platforms are valuable sources of information for patient opinion mining. In this paper, we have tackled three issues that come along with inconsistency analysis on PRWs: (1) Natural language processing of user-generated reviews, (2) the disagreement in polarity of review text and its corresponding numerical ratings (individual inconsistency) and (3) the differences in patients’ rating behavior for the same service category (e.g. ‘treatment’) expressed by varying grades on the entire data set (collective inconsistency). Thus, the basic idea is first to identify relevant opinion phrases that describe service categories and to determine their polarity. Subsequently, the particular phrase has to be assigned to its corresponding numerical rating category before checking the (dis-)agreement of polarity values. For this purpose, several local grammars for the pattern-based analysis as well as domain-specific dictionaries for the recognition of entities, aspects and polarity were applied on 593,633 physician reviews from both German PRWs jameda.de and docinsider.de. Furthermore, our research contributes to content quality improvement of PRWs because we provide a technique to detect inconsistent reviews that could be ignored for the computation of average ratings.}}, author = {{Geierhos, Michaela and Bäumer, Frederik Simon and Schulze, Sabine and Stuß, Valentina}}, booktitle = {{ECIS 2015 Completed Research Papers}}, isbn = {{9783000502842}}, location = {{Münster, Germany}}, publisher = {{Elsevier}}, title = {{{"I grade what I get but write what I think." Inconsistency Analysis in Patients' Reviews}}}, doi = {{10.18151/7217324}}, year = {{2015}}, } @techreport{1147, abstract = {{Der Erfahrungsaustausch zwischen Patienten findet verstärkt über Arztbewertungsportale statt. Dabei ermöglicht die Anonymität des Netzes ein weitestgehend ehrliches Beschwerdeverhalten, von dem das sensible Arzt-Patienten-Vertrauensverhältnis unbeschädigt bleibt. Im Rahmen des vorliegenden Beitrags wurden anonyme Arztbewertungen im Web 2.0 automatisiert ausgewertet, um Einflussfaktoren auf das Beschwerdeverhalten deutscher Patienten zu bestimmen und in der Gesellschaft vermeintlich etablierte „Patienten-Mythen“ aufzuklären. Die Aufdeckung von Irrtümern und Zufriedenheitsindikatoren soll längerfristig dazu dienen, Patientenäußerungen differenzierter zu interpretieren und somit zu einer nachhaltigen Verbesserung der Arzt-Patienten-Beziehung beizutragen.}}, author = {{Geierhos, Michaela and Schulze, Sabine and Bäumer, Frederik Simon}}, pages = {{18}}, publisher = {{Verbraucherzentrale NRW/Kompetenzzentrum Verbraucherforschung NRW}}, title = {{{Der zufriedene Patient 2.0: Analyse anonymer Arztbewertungen im Web 2.0}}}, doi = {{10.15501/kvfwp_3}}, volume = {{3}}, year = {{2015}}, } @inproceedings{1148, abstract = {{The individual search for information about physicians on Web 2.0 platforms can affect almost all aspects of our lives. People can directly access physician rating websites via web browsers or use any search engine to find physician reviews and ratings filtered by location resp. specialty. However, sometimes keyword search does not meet user needs because of the disagreement of users’ common terms queries for symptoms and the widespread medical terminology. In this paper, we present the prototype of a specialised search engine that overcomes this by indexing user-generated content (i.e., review texts) for physician discovery and provides automatic suggestions as well as an appropriate visualisation. On the one hand, we consider the available numeric physician ratings as sorting criterion for the ranking of query results. Furthermore, we extended existing ranking algorithms with respect to domain-specific types and physicians ratings on the other hand. We gathered more than 860,000 review texts and collected more than 213,000 physician records. A random test shows that about 19.7% of 5,100 different words in total are health- related and partly belong to consumer health vocabularies. Our evaluation results show that the query results fit user's particular health issues when seeking for physicians.}}, author = {{Bäumer, Frederik Simon and Dollmann, Markus and Geierhos, Michaela}}, booktitle = {{The 6th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2015) / The 5th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2015) / Affiliated Workshops}}, editor = {{Shakshuki, Elhadi M.}}, issn = {{18770509}}, keywords = {{Physician Discovery, Consumer Health Vocabulary, Common Terms Query}}, location = {{Berlin, Germany}}, pages = {{417--424}}, publisher = {{Elsevier}}, title = {{{Find a Physician by Matching Medical Needs described in your Own Words}}}, doi = {{10.1016/j.procs.2015.08.362}}, volume = {{63}}, year = {{2015}}, } @inbook{1149, abstract = {{The contacts a health care provider (HCP), like a physician, has to other HCPs is perceived as a quality characteristic by patients. So far, only the German physician rating website jameda.de gives information about the interconnectedness of HCPs in business networks. However, this network has to be maintained manually and is thus incomplete. We therefore developed a system for uncovering latent connectivity of HCPs in online reviews to provide users with more valuable information about their HCPs. The overall goal of this approach is to extend already existing business networks of HCPs by integrating connections that are newly discovered by our system. Our most recent evaluation results are promising: 70.8 % of the connections extracted from the reviews texts were correctly identified and in total 3,788 relations were recognized that have not been displayed in jameda.de’s network before.}}, author = {{Bäumer, Frederik Simon and Geierhos, Michaela and Schulze, Sabine}}, booktitle = {{Information and Software Technologies. 21st International Conference, ICIST 2015, Druskininkai, Lithuania, October 15-16, 2015. Proceedings}}, editor = {{Dregvaite, Giedre and Damasevicius, Robertas}}, isbn = {{978-3-319-24769-4}}, keywords = {{Latent Connectivity, Person Named Entity Recognition and Disambiguation, Health Care Provider Reviews}}, location = {{Druskininkai, Lithuania}}, pages = {{3--15}}, publisher = {{Springer}}, title = {{{A System for Uncovering Latent Connectivity of Health Care Providers in Online Reviews}}}, doi = {{10.1007/978-3-319-24770-0_1}}, volume = {{538}}, year = {{2015}}, } @inbook{1150, abstract = {{Patients 2.0 increasingly inform themselves about the quality of medical services on physician rating websites. However, little is known about whether the reviews and ratings on these websites truly reflect the quality of services or whether the ratings on these websites are rather influenced by patients’ individual rating behavior. Therefore, we investigate more than 790,000 physician reviews on Germany’s most used physician rating website jameda.de. Our results show that patients’ ratings do not only reflect treatment quality but are also influenced by treatment quality independent factors like age and complaint behavior. Hence, we provide evidence that users should be well aware of user specific rating distortions when intending to make their physician choice based on these ratings.}}, author = {{Geierhos, Michaela and Bäumer, Frederik Simon and Schulze, Sabine and Klotz, Caterina}}, booktitle = {{Modeling and Using Context. 9th International and Interdisciplinary Conference, CONTEXT 2015, Lanarca, Cyprus, November 2-6, 2015. Proceedings}}, editor = {{Christiansen, Henning and Stojanovic, Isidora and Papadopoulos, George A.}}, isbn = {{9783319255903}}, keywords = {{Health 2.0, Rating Behavior, Patient Opinion Mining on Physician Rating Websites}}, location = {{Larnaca, Cyprus}}, pages = {{159--171}}, publisher = {{Springer}}, title = {{{Understanding the Patient 2.0: Gaining Insight into Patients' Rating Behavior by User-generated Physician Review Mining}}}, doi = {{10.1007/978-3-319-25591-0_12}}, volume = {{9405}}, year = {{2015}}, } @inproceedings{231, abstract = {{Existing approaches towards service composition demand requirements of the customers in terms of service templates, service query profiles, or partial process models. However, addressed non-expert customers may be unable to fill-in the slots of service templates as requested or to describe, for example, pre- and postconditions, or even have difficulties in formalizing their requirements. Thus, our idea is to provide non-experts with suggestions how to complete or clarify their requirement descriptions written in natural language. Two main issues have to be tackled: (1) partial or full inability (incapacity) of non-experts to specify their requirements correctly in formal and precise ways, and (2) problems in text analysis due to fuzziness in natural language. We present ideas how to face these challenges by means of requirement disambiguation and completion. Therefore, we conduct ontology-based requirement extraction and similarity retrieval based on requirement descriptions that are gathered from App marketplaces. The innovative aspect of our work is that we support users without expert knowledge in writing their requirements by simultaneously resolving ambiguity, vagueness, and underspecification in natural language.}}, author = {{Geierhos, Michaela and Schulze, Sabine and Bäumer, Frederik Simon}}, booktitle = {{Proceedings of the 7th International Conference on Agents and Artificial Intelligence (ICAART), Special Session on Partiality, Underspecification, and Natural Language Processing (PUaNLP 2015)}}, editor = {{Loiseau, Stephane and Filipe, Joaquim and Duval, Béatrice and van den Herik, Jaap}}, isbn = {{ 978-989-758-073-4}}, pages = {{277--283}}, publisher = {{SciTePress - Science and Technology Publications}}, title = {{{What did you mean? Facing the Challenges of User-generated Software Requirements}}}, doi = {{10.5220/0005346002770283}}, year = {{2015}}, } @inbook{21905, author = {{Rumlich, Dominik}}, booktitle = {{CLIL Revisited: Eine kritische Analyse des gegenwärtigen Standes des bilingualen Sachfachunterrichts}}, editor = {{Rüschoff, Bernd and Sudhoff, Julian-Thorben and Wolff, Dieter}}, pages = {{309--330}}, publisher = {{Lang}}, title = {{{Zur affektiv-motivationalen Entwicklung von Lernenden im bilingualen Sachfachunterricht}}}, year = {{2015}}, } @article{21906, author = {{Rumlich, Dominik}}, journal = {{Diversität konkret}}, number = {{1}}, pages = {{1--28}}, title = {{{Selbst(bestimmt) sind die Lernenden! Ideen und Methoden für eine studierendenzentrierte Lernveranstaltung.}}}, volume = {{3}}, year = {{2015}}, } @misc{9695, author = {{Tönnies, Merle}}, booktitle = {{Journal of Contemporary Drama in English}}, number = {{2}}, pages = {{355--358}}, title = {{{Jürs-Munby, K. / Carroll, J. / Giles, S. (Hg.): Postdramatic Theatre and the Political}}}, volume = {{3}}, year = {{2015}}, } @article{6769, author = {{Tönnies, Merle}}, journal = {{Dramatic Minds. Performance, Cognition, and the Representation of Interiority}}, pages = {{243--260}}, publisher = {{Peter Lang}}, title = {{{Between Authenticity and Objectification: Narrating the Self in Contemporary British Drama}}}, year = {{2015}}, } @inbook{9231, author = {{Mildorf, Jarmila}}, booktitle = {{Dark Nights, Bright Lights}}, editor = {{Bach, Susanne and Degenring, Folkert}}, pages = {{57--70}}, publisher = {{de Gruyter}}, title = {{{‘Light of Life’: Gender, Place and Knowledge in H. G. Wells’ 'Ann Veronica'}}}, year = {{2015}}, } @article{9210, author = {{Mildorf, Jarmila}}, journal = {{Književna istorija / Literary History}}, pages = {{33--48}}, title = {{{Worth Pursuing? The Limits of Cognitive Narratology}}}, volume = {{XLVII}}, year = {{2015}}, } @inbook{9232, author = {{Mildorf, Jarmila}}, booktitle = {{Unreliable Narration and Trustworthiness: Intermedial and Interdisciplinary Perspectives}}, editor = {{Nünning, Vera}}, pages = {{395--413}}, publisher = {{de Gruyter}}, title = {{{Unreliability in Patient Narratives: From Clinical Assessment to Narrative Practice}}}, year = {{2015}}, } @inbook{1124, abstract = {{Finding information about people in the World Wide Web is one of the most common activities of Internet users. It is now impossible to manually analyze all this information and new approaches are needed that are capable of processing the large-scale heterogeneous data in order to extract the pertinent information. The Wikipedia community still puts much effort in manually adding structured data to biographical articles, the so-called {{Persondata}} template. Thanks to this kind of metadata, semantically-enriched information concerning the biographee (e.g. name, date of birth, place of birth) can be extracted and processed by search engines. But it is a rather time-consuming task and users quite often forget to add this template: some biographies contain persondata, others do not. There is considerably less work done on developing approaches to automatically enhance English Wikipedia biographies with persondata and therefore improve the quality of structured user contributions. Within this paper, we describe our method to automatically generate persondata from biographical information in Wikipedia articles.}}, author = {{Geierhos, Michaela}}, booktitle = {{Penser le Lexique-Grammaire}}, editor = {{Kakoyianni-Doa, Fryni}}, isbn = {{9782745325129}}, location = {{Nicosia, Cyprus}}, pages = {{411--420}}, publisher = {{Honoré Champion}}, title = {{{Towards a Local Grammar-based Persondata Generator for Wikipedia Biographies}}}, year = {{2014}}, } @inproceedings{1130, abstract = {{In this paper, we focus on the acronym representation, the concept of abbreviation of major terminology. To this end, we try to find the most efficient method to disambiguate the sense of the acronym. Comparing the various feature types, we found that using single noun (NN) overwhelmingly outperformed noun phrase (NP) base. Moreover, the result also showed that collocation information (CL) was not efficient for enhancing performance considering a huge extra data processing. We expect to apply the open knowledge base Wikipedia to scholarly service to enhance the quality of the local knowledge base and to develop value-added services.}}, author = {{Jeong, Do-Heon and Gim, Jangwon and Jung, Hanmin and Geierhos, Michaela and Bäumer, Frederik Simon}}, booktitle = {{Conference Proceedings of the 9th Asia Pacific International Conference on Information Science and Technology (APIC-IST 2014)}}, issn = {{20930542}}, location = {{Kathmandu, Nepal}}, pages = {{369--371}}, title = {{{Comparative study on disambiguating acronyms in the scientific papers using the open knowledge base}}}, year = {{2014}}, }