Traits of a Leader: User Influence Level Prediction through Sociolinguistic Modeling

• URL: http://arxiv.org/abs/2501.04046v1
• Date: Sun, 05 Jan 2025 22:37:19 GMT
• Title: Traits of a Leader: User Influence Level Prediction through Sociolinguistic Modeling
• Authors: Denys Katerenchuk, Rivka Levitan,
• Abstract summary: We develop a model that significantly outperforms the baseline by leveraging demographic and personality data. This approach consistently improves RankDCG scores across eight different domains.
• Score: 8.890331069484203
• License:
• Abstract: Recognition of a user's influence level has attracted much attention as human interactions move online. Influential users have the ability to sway others' opinions to achieve some goals. As a result, predicting users' level of influence can help to understand social networks, forecast trends, prevent misinformation, etc. However, predicting user influence is a challenging problem because the concept of influence is specific to a situation or a domain, and user communications are limited to text. In this work, we define user influence level as a function of community endorsement and develop a model that significantly outperforms the baseline by leveraging demographic and personality data. This approach consistently improves RankDCG scores across eight different domains.

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