Abstract
Understanding the social media audience is becoming increasingly important for social media analysis. This paper presents an approach that detects various audience attributes, including author location, demographics, behavior and interests. It works both for a variety of social media sources and for multiple languages. The approach has been implemented within IBM Watson Analytics for Social Media and creates author profiles for more than 300 different analysis domains every day.- Anthology ID:
- E17-3014
- Volume:
- Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- André Martins, Anselmo Peñas
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 53–56
- Language:
- URL:
- https://aclanthology.org/E17-3014
- DOI:
- Cite (ACL):
- Verena Henrich and Alexander Lang. 2017. Audience Segmentation in Social Media. In Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 53–56, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Audience Segmentation in Social Media (Henrich & Lang, EACL 2017)
- PDF:
- https://preview.aclanthology.org/naacl24-info/E17-3014.pdf