07/06/2021

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

Keith Cortis, Brian Davis

Keywords: Analysis of the relationship between social media and mainstream media, Qualitative and quantitative studies of social media, Subjectivity in textual data, sentiment analysis, polarity/opinion identification and extraction, linguistic analyses of social me

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.

 0
 0
 0
 0
This is an embedded video. Talk and the respective paper are published at ICWSM 2021 virtual conference. If you are one of the authors of the paper and want to manage your upload, see the question "My papertalk has been externally embedded..." in the FAQ section.

Comments

Post Comment
no comments yet
code of conduct: tbd

Similar Papers