%0 Journal Article
	%A Ashwaq Alsulami and  Jianhua Shao
	%D 2022
	%J International Journal of Humanities and Social Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 183, 2022
	%T Extracting Attributes for Twitter Hashtag Communities
	%U https://publications.waset.org/pdf/10012489
	%V 183
	%X Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.
	%P 171 - 178