Abstract
The ability to compose emerging topics from the data collected from multiple social media platforms can help individuals and organisations meet their business goals and improve decision-making, as such information can provide more complete and accurate information. However, existing research has mainly focused on analysing emerging topics from the posts and related data collected from a single social media platform. In this paper, we propose a framework referred to as Multi-source Social Topic Media Analysis (xSMA) framework to model, rank and semantically analyse emerging topics across various social media platforms. The implementation and evaluation of the xSMA framework using real-world datasets obtained from Twitter and Reddit are also described.
Original language | English |
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Title of host publication | Proceedings of the Australasian Computer Science Week Multiconference 2019 |
Editors | Tony Sahama, Ying Wang |
Place of Publication | New York NY USA |
Publisher | Association for Computing Machinery (ACM) |
Number of pages | 9 |
ISBN (Electronic) | 9781450366038 |
DOIs | |
Publication status | Published - 2019 |
Event | Australasian Workshop on Health Informatics and Knowledge Management (HIKM) 2019 - Sydney, Australia Duration: 29 Jan 2019 → 31 Jan 2019 Conference number: 12th https://web.archive.org/web/20190329212701/http://hikm.net.au/ |
Workshop
Workshop | Australasian Workshop on Health Informatics and Knowledge Management (HIKM) 2019 |
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Abbreviated title | HIKM 2019 |
Country/Territory | Australia |
City | Sydney |
Period | 29/01/19 → 31/01/19 |
Internet address |
Keywords
- Social media
- topic modelling
- topic ranking
- topic similarity