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Attention-based LSTM model with the Aspect information to solve financial opinion mining problem (WWW 2018 shared task1)

Germeval2017 Sentiment Detection ⭐ 11

Sentence Embeddings used in the GermEval-2017 Submission

Sentiment Analysis ⭐ 5

In this work, we aim to predict the intensity of user emotion (anger, fear, sadness and joy) contained in a sentence. This problem is more challenging than the task of classification into sentiment categories as the degree of emotion extraction needs deeper level of granularity. We have approached the solution with various techniques such as tfidf, lexicon based approaches, Word embeddings and LSTM networks. In this process, we found a few interesting observations regarding the behavior of diffe

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