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  1. Sentiment Annotation of Historic German Plays: An Empirical Study on Annotation Behavior
    Published: 2018
    Publisher:  CEUR-WS.org

    We present results of a sentiment annotation study in the context of historical German plays. Our annotation corpus consists of 200 representative speeches from the German playwright Gotthold Ephraim Lessing. Six annotators, five non-experts and one... more

     

    We present results of a sentiment annotation study in the context of historical German plays. Our annotation corpus consists of 200 representative speeches from the German playwright Gotthold Ephraim Lessing. Six annotators, five non-experts and one expert in the domain, annotated the speeches according to different sentiment annotation schemes. They had to annotate the differentiated polarity (very negative, negative, neutral, mixed, positive, very positive), the binary polarity (positive/negative) and the occurrence of eight basic emotions. After the annotation, the participants completed a questionnaire about their experience of the annotation process; additional feedback was gathered in a closing interview. Analysis of the annotations shows that the agreement among annotators ranges from low to mediocre. The non-expert annotators perceive the task as very challenging and report different problems in understanding the language and the context. Although fewer problems occur for the expert annotator, we cannot find any differences in the agreement levels among non-experts and between the expert and the non-experts. At the end of the paper, we discuss the implications of this study and future research plans for this area

     

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    Source: BASE Selection for Comparative Literature
    Language: German
    Media type: Conference object
    Format: Online
    DDC Categories: 800
    Subjects: sentiment analysis; sentiment annotation; drama; emotion analysis; computational linguistics
    Rights:

    info:eu-repo/semantics/openAccess

  2. Toward Multimodal Sentiment Analysis of Historic Plays: A Case Study with Text and Audio for Lessing’s Emilia Galotti
    Published: 2019
    Publisher:  CEUR-WS.org

    We present a case study as part of a work-in-progress project about multimodal sentiment analysis on historic German plays, taking Emilia Galotti by G. E. Lessing as our initial use case. We analyze the textual version and an audio version... more

     

    We present a case study as part of a work-in-progress project about multimodal sentiment analysis on historic German plays, taking Emilia Galotti by G. E. Lessing as our initial use case. We analyze the textual version and an audio version (audiobook). We focus on ready-to-use sentiment analysis methods: For the textual component, we implement a naive lexicon-based approach and another approach that enhances the lexicon by means of several NLP methods. For the audio analysis, we use the free version of the Vokaturi tool. We compare the results of all approaches and evaluate them against the annotations of a human expert, which serves as a gold standard. For our use case, we can show that audio and text sentiment analysis behave very differently: textual sentiment analysis tends to predict sentiment as rather negative and audio sentiment as rather positive. Compared to the gold standard, the textual sentiment analysis achieves accuracies of 56% while the accuracy for audio sentiment analysis is only 32%. We discuss possible reasons for these mediocre results and give an outlook on further steps we want to pursue in the context of multimodal sentiment analysis on historic plays.

     

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    Source: BASE Selection for Comparative Literature
    Language: English
    Media type: Conference object
    Format: Online
    DDC Categories: 800
    Subjects: computational literary studies; text mining; audio; audiobooks; drama; emotion analysis; Lessing; multimedia; multimodal; sentiment analysis
    Rights:

    info:eu-repo/semantics/openAccess