Multilingual Sentiment Analysis Resources

Multilingual Sentiment Analysis Benchmark Datasets

We offer the following benchmark datasets for download: Please refer to and cite the below papers for further details.

Multilingual Sentiment Vectors for Deep Sentiment Analysis

We learn sentiment embeddings by training different supervised models. The weights for a word across different models are concatenated into a single sentiment embedding vector for that word.
Method to create word embeddings capturing sentiment

Our sentiment vectors for the languages in the paper are available for download.

License: CC-BY-NC-SA 4.0 license (for non-commercial use)

For further languages or other uses, please get in touch with us.

Emotion Analysis Resources


Often, it is useful to go beyond just positive vs. negative towards fine-grained emotion analytics, e.g. when we want to know whether a customer is angry, disappointed, or terrified. We provide the following two resources.

AffectVec
Fine-grained emotion intensity scores for 70,000 English words covering over 200 emotions
Emoji resources
Emoji-based emotion vectors for words

References

DCM-CNN neural model to exploit sentiment embeddings

For more information about the datasets and method, please consult our publications:

Cross-Lingual Propagation for Deep Sentiment Analysis  BibTeX
Xin Dong, Gerard de Melo (2018)
In: Proc. AAAI 2018. AAAI Press.
Acceptance rate: 25%

A Helping Hand: Transfer Learning for Deep Sentiment Analysis  BibTeX
Xin Dong, Gerard de Melo (2018)
In: Proc. ACL 2018.
Acceptance rate: 24.9%

 

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