User-Centric Analysis & Improvement of Web Page Engagement with User Generated Content
The project analyses the time users spend on web pages of derStandard.at and how this relates to what people say and how the tone is in forum postings. A major aim is to investigate whether and how various linguistic and semantic aspects of the user-generated content influence the time users spend in a forum as readers and what motivates users to become active posters. A particular focus lies on female posters. While the percentage of female and male readers of derStandard.at is near equal (45% to 55%), there is a large gender mismatch in active posters, i.e., only 20% of those who write in forums are female). Therefore, important goals for the project are to find out reasons for this gender disparity and to take measures to encourage female contributions. Methods of data science and natural language processing are employed to identify correlations between forum dwell time, and linguistic and semantic properties of forum contributions, including gender-fair language use. Deep learning approaches are applied to identify mysogynic content. All this helps forum moderators to counteract female discrimination in the web.
FemPower IKT 2018