Data Set Information:

documents are first obtained via a Web search using AMIEI: an integrated platform for delivering enterprise intelligence, developed by AMI Software ([Web link]) with the following query: ``dsk'' OR ``strauss-kahn'' OR ``strauss-khan''.

NYSK dataset was used to extract topic-sentiment correlation and evolution over time but may be used for other text mining tasks like topic extraction, sentiment analysis, etc.

Attribute Information:

documents are then filtered and presented in XML format. All XML fields are self explanatory.

Relevant Papers:

(1) Mohamed Dermouche, Julien Velcin, Leila Khouas, and Sabine Loudcher. A Joint Model for Topic-Sentiment Evolution over Time. In Proceedings of The IEEE 14th International Conference on Data Mining (ICDM’2014), pages 773–778, Shenzhen, China, 2014. IEEE Computer Society.

(2) Mohamed Dermouche, Leila Khouas, Julien Velcin, and Sabine Loudcher. A Joint Model for Topic-Sentiment Modeling from Text. In Proceedings of The 30th ACM/SIGAPP Symposium On Applied Computing (SAC’2015), pages 819--824, Salamanca, Spain, 2015. ACM.

Citation Request:

Please refer to the Machine Learning Repository's citation policy

- Aurélien Lauf (alu '@' amisw.com)
- Leila Khouas (lkh '@' amisw.com)
- Mohamed Dermouche (mde '@' amisw.com)