Aiding Sentiment Evaluation with Social Network
نویسندگان
چکیده
One challenge for sentiment analysis as well as many other natural language processing task is the language variation. In this project, based on the intuition of language homophily, we aim to solve this problem by combing social network information. We propose a new model that measure the interaction between author embedding and sentence words’ embeddings. This model is based on the current state-of-the-art methodology that does not consider social network information. The authors’ embeddings are pretrained with three different yet most popular network node embedding methods, and their performances are compared.
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