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Odi et Amo. Creating, Evaluating and Extending Sentiment Lexicons for Latin
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Abstract:
Sentiment lexicons are essential for developing automatic sentiment analysis systems, but the resources currently available mostly cover modern languages. Lexicons for ancient languages are few and not evaluated with high-quality gold standards. However, the study of attitudes and emotions in ancient texts is a growing field of research which poses specific issues (e.g., lack of native speakers, limited amount of data, unusual textual genres for the sentiment analysis task, such as philosophical or documentary texts) and can have an impact on the work of scholars coming from several disciplines besides computational linguistics, e.g. historians and philologists. The work presented in this paper aims at providing the research community with a set of sentiment lexicons built by taking advantage of manually-curated resources belonging to the long tradition of Latin corpora and lexicons creation. Our interdisciplinary approach led us to release: i) two automatically generated sentiment lexicons; ii) a Gold Standard developed by two Latin language and culture experts; iii) a Silver Standard in which semantic and derivational relations are exploited so to extend the list of lexical items of the Gold Standard. In addition, the evaluation procedure is described together with a first application of the lexicons to a Latin tragedy.
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Keyword:
Sentiment analysis; Settore L-LIN/01 - GLOTTOLOGIA E LINGUISTICA
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URL: https://doi.org/10.5281/zenodo.3862149 http://hdl.handle.net/10807/154884 http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.376.pdf
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82 |
MultiEmotions-it: A new dataset for opinion polarity and emotion analysis for Italian
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Sprugnoli, R. (orcid:0000-0001-6861-5595). - : Accademia University Press, 2020. : country:ITA, 2020. : place:Torino, 2020
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83 |
Techniques for improving the labelling process of sentiment analysis in the Saudi stock market
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84 |
Analysis of the relationship between Saudi twitter posts and the Saudi stock market
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85 |
Identifying Mubasher software products through sentiment analysis of Arabic tweets
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86 |
Visualising Arabic sentiments and association rules in financial text
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87 |
Using Multi-granular Fuzzy Linguistic Modelling Methods to Represent Social Networks Related Information in an Organized Way
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88 |
Arabic-English Google Translation Evaluation and Arabic Sentiment Analysis
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89 |
English Studies and Literary Education in the Era of Media Manipulation: Context, Perceptions, Feelings and Challenges
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90 |
Predicting Students’ College Drop Out and Departure Decisions by Analyzing their Campus-Based Social Network Text Messages
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91 |
A Study on the Contributions of Domain-Specific Semantics Towards Aspect-Based Sentiment Analysis
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In: Master's Theses (2020)
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Sentiment Analysis of Textual Content in Social Networks. From Hand-Crafted to Deep Learning-Based Models
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In: TDX (Tesis Doctorals en Xarxa) (2020)
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This video is sponsored : text and sentiment analysis of YouTube health-related vlog comments and brand endorsement effectiveness
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95 |
Sentiment Lexicon Induction and Interpretable Multiple-instance Learning in Financial Markets
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96 |
Exploring Explicit and Implicit Feature Spaces in Natural Language Processing Using Self-Enrichment and Vector Space Analysis
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In: Electronic Thesis and Dissertation Repository (2020)
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Towards Subjective Multimedia Summarization Framework for Sporting Event in the Context of Digital Twins
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98 |
Domain specific lexicon generation through sentiment analysis
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99 |
Using Keystroke Dynamics in a Multi-Agent System for User Guiding in Online Social Networks
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100 |
A Twitter Political Corpus of the 2019 10N Spanish Election
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