A Dataset of Multidimensional and Multilingual Social Opinions for Malta’s Annual Government Budget

Authors

  • Keith Cortis ADAPT Centre
  • Brian Davis ADAPT Centre

Keywords:

Subjectivity in textual data; sentiment analysis; polarity/opinion identification and extraction, linguistic analyses of social media behavior, Social innovation and effecting change through social media, Analysis of the relationship between social media and mainstream media, Qualitative and quantitative studies of social media

Abstract

This paper presents three high quality social opinion datasets in the socio-economic domain, specifically Malta's annual Government Budgets of 2018, 2019 and 2020. They contain over 6,000 online posts of user-generated content in English and/or Maltese, gathered from newswires and social networking services. These have been annotated for multiple opinion dimensions, namely subjectivity, sentiment polarity, emotion, sarcasm and irony, and in terms of negation, topic and language. These datasets are a valuable resource for developing Opinion Mining tools and Language Technologies, and can be used as a baseline for assessing the state-of-the-art and for developing new advanced analytical methods for Opinion Mining. Moreover, they can be used for policy formulation, policy-making, decision-making and decision-taking. This research can also support similar initiatives in other countries, studies in the socio-economic domain and applied in other areas, such as Politics, Finance, Marketing, Advertising, Sales and Education.

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Published

2021-05-22

How to Cite

Cortis, K., & Davis, B. (2021). A Dataset of Multidimensional and Multilingual Social Opinions for Malta’s Annual Government Budget. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 971-981. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18120