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 |
|---|---|
| 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/ |
Conference
| Conference | Australasian Workshop on Health Informatics and Knowledge Management (HIKM) 2019 |
|---|---|
| Abbreviated title | HIKM 2019 |
| Country | Australia |
| City | Sydney |
| Period | 29/01/19 → 31/01/19 |
| Internet address |
Keywords
- Social media
- topic modelling
- topic ranking
- topic similarity
Cite this
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Analysing emerging topics across multiple social media platforms. / Pokharel, Rashmi; Delir Haghighi, Pari; Jayaraman, Prem; Georgakopoulos, Dimitrios .
Proceedings of the Australasian Computer Science Week Multiconference 2019. ed. / Tony Sahama; Ying Wang. New York NY USA : Association for Computing Machinery (ACM), 2019. 16.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Analysing emerging topics across multiple social media platforms
AU - Pokharel, Rashmi
AU - Delir Haghighi, Pari
AU - Jayaraman, Prem
AU - Georgakopoulos, Dimitrios
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Social media
KW - topic modelling
KW - topic ranking
KW - topic similarity
UR - http://www.scopus.com/inward/record.url?scp=85061253039&partnerID=8YFLogxK
U2 - 10.1145/3290688.3290720
DO - 10.1145/3290688.3290720
M3 - Conference Paper
BT - Proceedings of the Australasian Computer Science Week Multiconference 2019
A2 - Sahama, Tony
A2 - Wang, Ying
PB - Association for Computing Machinery (ACM)
CY - New York NY USA
ER -