Make Me Laugh: A Recommendation System for Humoristic Content on the World Wide Web
Herausgeber Sammlung:
Weisbecker, Anette; Burmester, Michael; Schmidt, Albrecht
Titel Konferenzpublikation:
Mensch und Computer 2015 – Workshopband
Reihentitel:
Mensch & Computer – Tagungsbände / Proceedings
Konferenztitel:
Mensch und Computer (2015, Stuttgart)
Tagungsort:
Stuttgart, Germany
Jahr der Konferenz:
2015
Datum Beginn der Konferenz:
06.09.2015
Datum Ende der Konferenz:
09.09.2015
Verlagsort:
Berlin ; Boston
Verlag:
De Gruyter
Jahr:
2015
Sprache:
Englisch
Abstract:
Humoristic content is an inherent part of the World Wide Web and increasingly consumed for micro-entertainment. However, humor is often highly individual and depends on background knowledge and context. This paper presents an approach to recommend humoristic content fitting each individual user's taste and interests. In a field study with 150 participants over four weeks, users rated content with a 0-10 scale on a humor website. Based on this data, we train and apply a Collaborative Filtering (CF) algorithm to assess individual humor and recommend fitting content. Our study shows that users rate recommended content 22.6% higher than randomly chosen content. «
Humoristic content is an inherent part of the World Wide Web and increasingly consumed for micro-entertainment. However, humor is often highly individual and depends on background knowledge and context. This paper presents an approach to recommend humoristic content fitting each individual user's taste and interests. In a field study with 150 participants over four weeks, users rated content with a 0-10 scale on a humor website. Based on this data, we train and apply a Collaborative Filtering (C... »