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Auflistung nach Schlagwort "Sentiment Analysis"

1 - 7 von 7
  • Workshopbeitrag
    Collaborative Manufacturing Process Redesign Using Sentiment Analysis
    (Mensch und Computer 2021 - Workshopband, 2021) Softic, Selver; Lüftenegger, Egon; Stojic, Aleksandar
    We present a novel tool called SentiProMo which uses sentiment analysis on collaborative comments collected during the design phase of business and manufacturing processes. This method involves the implicit information of sentiment hidden behind the suggestions for the process improvements. To discover and utilize the sentiment for process redesign we trained and tested a sentiment analysis module as part of our software. This module classifies and scores the sentiment of comments and acts as a part of SentiProMo tool for role based BPMN modeling and annotation. In order to evaluate the usability of the proposed software we tested it with a specific scenario including tasks with representative test persons. For this purpose we used standardized surveys like Computer System Usability Questionnaire (CSUQ) and Nielsen’s Heuristic model (NHE) to obtain the insights on usability of the system.
  • Workshopbeitrag
    Herausforderungen für Sentiment Analysis-Verfahren bei literarischen Texten
    (INF-DH-2018, 2018) Schmidt, Thomas; Burghardt, Manuel; Wolff, Christian
    In diesem Beitrag wird über die Ergebnisse eines laufenden Digital Humanities-Projekt zur Sentiment Analysis in literarischen Texten berichtet und die Implikation von diesem diskutiert. In dem Projekt werden verschiedene Methoden der Sentiment Analysis auf Texte historischer Dramen des 18. Jahrhunderts von G. E. Lessing implementiert und gegeneinander evaluiert. Zur Evaluation wurde ein von Menschen bezüglich Sentiment annotiertes Testkorpus erstellt. Basierend auf den ersten Erfahrungen des Projekts diskutieren wir über Probleme und Herausforderungen, die sich aus der Perspektive der Informatik zur Sentiment Analysis historischer Dramen ergaben. Es wird deut-lich, dass bestehende Standardlösungen der Sentiment Analysis für dieses spezifische Szenario nicht ohne Weiteres anwendbar sind. Vielmehr ist die Informatik gefordert, die bestehenden Methoden anzupassen, weiterzuentwickeln und sich mit besonderen Eigenheiten der Textform historischer literarischer Texte auseinanderzusetzen.
  • Konferenzbeitrag
    Inter-Rater Agreement and Usability: A Comparative Evaluation of Annotation Tools for Sentiment Annotation
    (INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (Workshop-Beiträge), 2019) Schmidt, Thomas; Winterl, Brigitte; Maul, Milena; Schark, Alina; Vlad, Andrea; Wolff, Christian
    We present the results of a comparative evaluation study of five annotation tools with 50 participants in the context of sentiment and emotion annotation of literary texts. Ten participants per tool annotated 50 speeches of the play Emilia Galotti by G. E. Lessing. We evaluate the tools via standard usability and user experience questionnaires, by measuring the time needed for the annotation, and via semi-structured interviews. Based on the results we formulate a recommendation. In addition, we discuss and compare the usability metrics and methods to develop best practices for tool selection in similar contexts. Furthermore, we also highlight the relationship between inter-rater agreement and usability metrics as well as the effect of the chosen tool on annotation behavior.
  • Konferenzbeitrag
    On the Importance of Subtext in Recommender Systems
    (i-com: Vol. 14, No. 1, 2015) Grasch, Peter; Felfernig, Alexander
    Conversational recommender systems have been shown capable of allowing users to navigate even complex and unknown application domains effectively. However, optimizing preference elicitation remains a largely unsolved problem. In this paper we introduce SPEECHREC, a speech-enabled, knowledge-based recommender system, that engages the user in a natural-language dialog, identifying not only purely factual constraints from the users’ input, but also integrating nuanced lexical qualifiers and paralinguistic information into the recommendation strategy. In order to assess the viability of this concept, we present the results of an empirical study where we compare SPEECHREC to a traditional knowledge-based recommender system and show how incorporating more granular user preferences in the recommendation strategy can increase recommendation quality, while reducing median session length by 46 %.
  • Konferenzbeitrag
    Public and Expert Insights into Generative AI: The potential for the Financial Industry
    (INFORMATIK 2024, 2024) Zacharias, Jan
    In the last few years, generative artificial intelligence (gen AI) has become a success factor in various sectors, including the financial industry. Understanding how the industry perceives gen AI is vital for its successful integration. Therefore, we conducted a mixed-methods study consisting of sentiment and subjectivity analyses of finance-related Reddit discussions, combined with expert interviews from global financial institutions. Whereas the public sentiment has a cautious optimism, experts express both strong support and concerns about gen AI implementations in financial institutions. This study contributes to the academic and practical understanding of gen AI’s real-world implications, highlighting the need for well-considered implementation strategies in the financial industry.
  • Konferenzbeitrag
    Sentiment Analysis of Participants Interactions in a Hackathon Context: The Example of a Slack Corpus
    (Mensch und Computer 2022 - Tagungsband, 2022) Feislachen, Sarah; Garus, Philip; Wang, Hong; Podkolin, Eduard; Schlüter, Sarah; Schulze Bernd, Nadine; Nolte, Alexander; Manske, Sven; Chounta, Irene-Angelica
    This paper presents the analysis of participants’ interactions during an online hackathon using Natural Language Processing (NLP) techniques. In particular, we explored the communication of groups facilitated by Slack focusing on the use of emojis. Our findings suggest that most used emojis are positive, while negative emojis appeared rarely. Sentiment of written messages was overall positive and could be linked to topics such as motivation or achievements. Topics about participants’ disappointment regarding their progress or the hackathon organization, technical issues and criticism were associated with negative sentiment. We envision that our work offers insights regarding online communication in group and collaborative contexts with an emphasis on group work and interest-based activities.
  • Konferenzbeitrag
    Understanding Trending Topics in Twitter
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband, 2017) Kahlert, Roland; Liebeck, Matthias; Cornelius, Joseph
    Many events, for instance in sports, political events, and entertainment, happen all over the globe all the time. It is difficult and time consuming to notice all these events, even with the help of different news sites. We use tweets from Twitter to automatically extract information in order to understand hashtags of real-world events. In our paper, we focus on the topic identification of a hashtag, analyze the expressed positive, neutral, and negative sentiments of users, and further investigate the expressed emotions. We crawled English tweets from 24 hashtags and report initial investigation results.