Paper: You%ve Got Answers: Towards Personalized Models for Predicting Success in Community Question Answering

ACL ID P08-2025
Title You%ve Got Answers: Towards Personalized Models for Predicting Success in Community Question Answering
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

Question answering communities such as Ya- hoo! Answers have emerged as a popular al- ternative to general-purpose web search. By directly interacting with other participants, in- formation seekers can obtain specific answers to their questions. However, user success in obtaining satisfactory answers varies greatly. We hypothesize that satisfaction with the con- tributed answers is largely determined by the asker’s prior experience, expectations, and personal preferences. Hence, we begin to de- velop personalized models of asker satisfac- tion to predict whether a particular question author will be satisfied with the answers con- tributed by the community participants. We formalize this problem, and explore a variety of content, structure, and interaction features for this task using sta...