Social Media-Based Expertise Evidence
Fulltext URI
Document type
Additional Information
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Social media provides a fertile ground for expertise location. The public nature of the data supports expertise inference with little privacy infringement and, in addition, presentation of direct and detailed evidence for an expert’s skillfulness in the queried topic. In this work, we study the use of social media for expertise evidence. We conducted two user surveys of enterprise social media users within a large global organization, in which participants were asked to rate anonymous experts based on artificial and real evidence originating from different types of social media data. Our results indicate that the social media data types perceived most convincing as evidence are not necessarily the ones from which expertise can be inferred most precisely or effectively. We describe these results in detail and discuss implications for designers and architects of expertise location systems.
Description
Keywords
Citation
URI
URI
Endorsement
Review
Supplemented By
Referenced By
Number of citations to item: 4
- Ido Guy (2018): People Recommendation on Social Media, In: Lecture Notes in Computer Science, doi:10.1007/978-3-319-90092-6_15
- Ido Guy (2015): The Role of User Location in Personalized Search and Recommendation, In: Proceedings of the 9th ACM Conference on Recommender Systems, doi:10.1145/2792838.2799502
- Ido Guy, Luiz Pizzato (2016): People Recommendation Tutorial, In: Proceedings of the 10th ACM Conference on Recommender Systems, doi:10.1145/2959100.2959196
- Raya Horesh, Kush R. Varshney, Jinfeng Yi (2016): Information retrieval, fusion, completion, and clustering for employee expertise estimation, In: 2016 IEEE International Conference on Big Data (Big Data), doi:10.1109/bigdata.2016.7840746