WSSA: Weakly Supervised Semantic-based approach for Sentiment Analysis

Author:

Mammar Kouadri Wissam1,Benbernou Salima1,Ouziri Mourad1,Ben Amor Iheb2

Affiliation:

1. University Paris City (LIPADE), France

2. IMBA CONSULTING, France

Publisher

ACM

Reference14 articles.

1. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic;Bach H.;J. Mach. Learn. Res.,2017

2. SenticNet 5: Discovering Conceptual Primitives for Sentiment Analysis by Means of Context Embeddings

3. Weakly Supervised Induction of Affective Events by Optimizing Semantic Consistency

4. Andrea Esuli and Fabrizio Sebastiani . 2006 . Sentiwordnet: A publicly available lexical resource for opinion mining.. In LREC, Vol. 6. Citeseer, 417–422. Andrea Esuli and Fabrizio Sebastiani. 2006. Sentiwordnet: A publicly available lexical resource for opinion mining.. In LREC, Vol. 6. Citeseer, 417–422.

5. Fangxiaoyu Feng Yinfei Yang Daniel Cer Naveen Arivazhagan and Wei Wang. 2020. Language-agnostic bert sentence embedding. arXiv preprint arXiv:2007.01852(2020). Fangxiaoyu Feng Yinfei Yang Daniel Cer Naveen Arivazhagan and Wei Wang. 2020. Language-agnostic bert sentence embedding. arXiv preprint arXiv:2007.01852(2020).

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