Predicting the Industry of Users on Social Media [article]

Konstantinos Pappas, Rada Mihalcea
2016 arXiv   pre-print
Automatic profiling of social media users is an important task for supporting a multitude of downstream applications. While a number of studies have used social media content to extract and study collective social attributes, there is a lack of substantial research that addresses the detection of a user's industry. We frame this task as classification using both feature engineering and ensemble learning. Our industry-detection system uses both posted content and profile information to detect a
more » ... ser's industry with 64.3% accuracy, significantly outperforming the majority baseline in a taxonomy of fourteen industry classes. Our qualitative analysis suggests that a person's industry not only affects the words used and their perceived meanings, but also the number and type of emotions being expressed.
arXiv:1612.08205v1 fatcat:rf5ybj6trzbefopxbodeyh5aey