A Fully Automated Approach for Arabic Slang Lexicon Extraction from Microblogs
AbstractWith the rapid increase in the volume of Arabic opinionated posts on different social media forums, comes an increased demand for Arabic sentiment analysis tools and resources. Social media posts, especially those made by the younger generation, are usually written using colloquial Arabic and include a lot of slang, many of which evolves over time. While some work has been carried out to build modern standard Arabic sentiment lexicons, these need to be supplemented with dialectical terms and continuously updated with slang. This paper proposes a fully automated approach for building a dialectical/slang subjectivity lexicon for use in Arabic Sentiment analysis using lexico-syntactic patterns. Since existing Arabic part of speech taggers and other morphological resources have been found to handle colloquial Arabic very poorly, the presented approach does not employ any such tools, allowing the presented approach to generalize across dialects with some minor modifications. Results of experiments, that targeted Egyptian Arabic, show the approach’s ability to detect subjective internet slang represented by single words or by multi-word expressions, as well as classifying the polarity of these with a high degree of precision.KeywordsSentiment AnalysisSentiment LexiconModern Standard ArabicSpeech TaggerMultiword ExpressionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.