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  • × theme_ss:"Inhaltsanalyse"
  1. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment strength detection for the social web (2012) 0.00 
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    Abstract
    Sentiment analysis is concerned with the automatic extraction of sentiment-related information from text. Although most sentiment analysis addresses commercial tasks, such as extracting opinions from product reviews, there is increasing interest in the affective dimension of the social web, and Twitter in particular. Most sentiment analysis algorithms are not ideally suited to this task because they exploit indirect indicators of sentiment that can reflect genre or topic instead. Hence, such algorithms used to process social web texts can identify spurious sentiment patterns caused by topics rather than affective phenomena. This article assesses an improved version of the algorithm SentiStrength for sentiment strength detection across the social web that primarily uses direct indications of sentiment. The results from six diverse social web data sets (MySpace, Twitter, YouTube, Digg, Runners World, BBC Forums) indicate that SentiStrength 2 is successful in the sense of performing better than a baseline approach for all data sets in both supervised and unsupervised cases. SentiStrength is not always better than machine-learning approaches that exploit indirect indicators of sentiment, however, and is particularly weaker for positive sentiment in news-related discussions. Overall, the results suggest that, even unsupervised, SentiStrength is robust enough to be applied to a wide variety of different social web contexts.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.163-173
    Type
    a
  2. Saif, H.; He, Y.; Fernandez, M.; Alani, H.: Contextual semantics for sentiment analysis of Twitter (2016) 0.00 
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    Abstract
    Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.
    Source
    Information processing and management. 52(2016) no.1, S.5-19
    Type
    a
  3. Xie, H.; Li, X.; Wang, T.; Lau, R.Y.K.; Wong, T.-L.; Chen, L.; Wang, F.L.; Li, Q.: Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy (2016) 0.00 
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    Abstract
    In recent years, there has been a rapid growth of user-generated data in collaborative tagging (a.k.a. folksonomy-based) systems due to the prevailing of Web 2.0 communities. To effectively assist users to find their desired resources, it is critical to understand user behaviors and preferences. Tag-based profile techniques, which model users and resources by a vector of relevant tags, are widely employed in folksonomy-based systems. This is mainly because that personalized search and recommendations can be facilitated by measuring relevance between user profiles and resource profiles. However, conventional measurements neglect the sentiment aspect of user-generated tags. In fact, tags can be very emotional and subjective, as users usually express their perceptions and feelings about the resources by tags. Therefore, it is necessary to take sentiment relevance into account into measurements. In this paper, we present a novel generic framework SenticRank to incorporate various sentiment information to various sentiment-based information for personalized search by user profiles and resource profiles. In this framework, content-based sentiment ranking and collaborative sentiment ranking methods are proposed to obtain sentiment-based personalized ranking. To the best of our knowledge, this is the first work of integrating sentiment information to address the problem of the personalized tag-based search in collaborative tagging systems. Moreover, we compare the proposed sentiment-based personalized search with baselines in the experiments, the results of which have verified the effectiveness of the proposed framework. In addition, we study the influences by popular sentiment dictionaries, and SenticNet is the most prominent knowledge base to boost the performance of personalized search in folksonomy.
    Source
    Information processing and management. 52(2016) no.1, S.61-72
    Type
    a
  4. Hjoerland, B.: Subject (of documents) (2016) 0.00 
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    Abstract
    This article presents and discusses the concept "subject" or subject matter (of documents) as it has been examined in library and information science (LIS) for more than 100 years. Different theoretical positions are outlined and it is found that the most important distinction is between document-oriented views versus request-oriented views. The document-oriented view conceive subject as something inherent in documents, whereas the request-oriented view (or the policy based view) understand subject as an attribution made to documents in order to facilitate certain uses of them. Related concepts such as concepts, aboutness, topic, isness and ofness are also briefly presented. The conclusion is that the most fruitful way of defining "subject" (of a document) is the documents informative or epistemological potentials, that is, the documents potentials of informing users and advance the development of knowledge.
    Content
    Contents: 1. Introduction; 2. Theoretical views: 2.1 Charles Ammi Cutter (1837-1903), 2.2 S. R. Ranganathan (1892-1972), 2.3 Patrick Wilson (1927-2003), 2.4 "Content oriented" versus "request oriented" views, 2.5 Issues of subjectivity and objectivity, 2.6 The subject knowledge view, 2.7 Other views and definitions; 3. Related concepts: 3.1 Words versus concepts versus subjects, 3.2 Aboutness, 3.3 Topic, 3.4 Isness, 3.5 Ofness, 3.6 Theme.
    Type
    a
  5. Caldera-Serrano, J.: Thematic description of audio-visual information on television (2010) 0.00 
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    Source
    Aslib proceedings. 62(2010) no.2, S.202-209
    Type
    a
  6. Franke-Maier, M.; Harbeck, M.: Superman = Persepolis = Naruto? : Herausforderungen und Probleme der formalen und inhaltlichen Vielfalt von Comics und Comicforschung für die Regensburger Verbundklassifikation (2016) 0.00 
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    Source
    o-bib: Das offene Bibliotheksjournal. 3(2016) Nr.4, S.243-256
    Type
    a
  7. Bi, Y.: Sentiment classification in social media data by combining triplet belief functions (2022) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 73(2022) no.7, S.968-991
    Type
    a
  8. Wersig, G.: Inhaltsanalyse : Einführung in ihre Systematik und Literatur (1968) 0.00 
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    Pages
    45 S
  9. Computergestützte Inhaltsanalyse in der empirischen Sozialforschung (1983) 0.00 
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    314 S
  10. Gervereau, L.: Voir, comprendre, analyser les images (1994) 0.00 
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    191 S
  11. Kessel, K.: Who's afraid of the big, bad uktena mster? : subject cataloging for images (2016) 0.00 
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    Abstract
    This article describes the difference between cataloging images and cataloging books, the obstacles to including subject data in image cataloging records and how these obstacles can be overcome to make image collections more accessible. I call for participants to help create a subject authority reference resource for non-Western art. This article is an expanded and revised version of a presentation for the 2016 Joint ARLIS/VRA conference in Seattle.
    Type
    a
  12. Mayring, P.: Qualitative Inhaltsanalyse : Grundlagen und Techniken (1990) 0.00 
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    Abstract
    "Inhaltsanalyse will: Kommunikation analysieren, fixierte Kommunikation analysieren, dabei systematisch vorgehen, das heißt regelgeleitet vorgehen, das heißt auch theoriegeleitet vorgehen, mit dem Ziel, Rückschlüsse auf bestimmte Aspekte der Kommunikation zu ziehen" (S.11)
    Pages
    118 S
  13. Ackermann, A.: Zur Rolle der Inhaltsanalyse bei der Sacherschließung : theoretischer Anspruch und praktische Wirklichkeit in der RSWK (2001) 0.00 
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    68 S. + Anlagen.
  14. Piekara, F.H.: Wie idiosynkratisch ist Wissen? : Individuelle Unterschiede im Assoziieren und bei der Anlage und Nutzung von Informationssystemen (1988) 0.00 
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  15. Früh, W.: Inhaltsanalyse (2001) 0.00 
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  16. Lebrecht, H.: Methoden und Probleme der Bilderschließung am Beispiel des verteilten digitalen Bildarchivs Prometheus (2003) 0.00 
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  17. Lebrecht, H.: Methoden und Probleme der Bilderschließung (2003) 0.00 
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  18. Scholz, O.R.: Bild, Darstellung, Zeichen : Philosophische Theorien bildlicher Darstellung (2004) 0.00 
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  19. Bös, K.: Aspektorientierte Inhaltserschließung von Romanen und Bildern : ein Vergleich der Ansätze von Annelise Mark Pejtersen und Sara Shatford (2012) 0.00 
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