Leveraging Personalized Sentiment Lexicons for Sentiment Analysis

ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval Virtual Event Norway September, 2020, pp. 109-112, 2020.

Cited by: 0|Bibtex|Views20|DOI:https://doi.org/10.1145/3409256.3409850
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

We propose a novel personalized approach for the sentiment analysis task. The approach is based on the intuition that the same sentiment words can carry different sentiment weights for different users. For each user, we learn a language model over a sentiment lexicon to capture her writing style. We further correlate this user-specific la...More

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