Output details
11 - Computer Science and Informatics
Aston University
Output title
Joint sentiment/topic model for sentiment analysis
Type
E - Conference contribution
Name of conference/published proceedings
CIKM '09 Proceedings of the 18th ACM conference on Information and knowledge management
Volume number
-
Issue number
-
First page of article
375
ISSN of proceedings
-
Year of publication
2009
Number of additional authors
1
Additional information
<22> The research represents a breakthrough in simultaneously detecting topics and topic-associated sentiments from text without the use of labelled data. Since the proposal of the joint sentiment-topic (JST) model, there have been several papers extending JST (e.g., Jo and Oh, 2011, DOI 10.1145/1935826.1935932 and Ramage et al., 2011, DOI 10.1145/2020408.2020481).
The model has been integrated into Luxid Skilled Cartridge, a text mining product developed by TEMIS, a text analytics company with 7 branches, in an EC-FP7 project, ROBUST (grant number 257859). TEMIS is discussing commercialising JST (Stefan Geißler, Managing Director of TEMIS Germany, stefan.geissler@temis.com) with Aston.
Interdisciplinary
-
Cross-referral requested
-
Research group
B - Computer Science Research Group
Citation count
57
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
