A Word Embedding Sentiment Scorer Of Many Emotions (AWESSOME) is a framework with the purpose of predicting the sentiment intensity of words and sentences (e.g phrases, tweets).

  • Paper : Amal Htait & Leif Azzopardi. "AWESSOME: An UnsupervisedSentiment Intensity Scoring Frameworkusing Neural Word Embeddings". ECIR 2021.
  • Download:

  •   DataMirror

    A tool that enables social network users to aggregate their online data so that they can search, browse and visualise what they have put online.

  • Paper : Amal Htait, Leif Azzopardi, Emma Nicol, and Wendy Moncur. "Reflecting on One's Data Self: A Tool for Social Media Users to Explore Their Digital Footprint". SIGIR 2020.
  • Download:

  •   ASID

    The "Adapted Sentiment Intensity Detector" is a Software to detect or predict sentiment intensity in text, at words level. It is adapted to certain domains, specified as parameters in command line. This tool is adapted to the following domains and languages:
    • - General Tweets in English Language
    • - General Tweets in Arabic Language
    • - Tweets about public transport in French Language
    • - Book Reviews in English Language
  • Paper : Amal Htait, Sébastien Fournier, and Patrice Bellot. "Sentiment Analysis and Sentence Classification in Long Book-Search Queries". CICLing 2019.
  • Download:

  •   NormAFE

    The Software creates dictionaries for micro-blogs normalisation, in a form of pairs of misspelled word with its standard-form word, in the languages: Arabic, French and English. It is based on an unsupervised method for text normalisation using distributed representations of words, known also as "word embedding".

  • Paper : Amal Htait, Sébastien Fournier, and Patrice Bellot. "Unsupervised Creation of Normalisation Dictionaries for Micro-Blogs in Arabic, French and English". Computación y Sistemas 2018.
  • Download: