Human or Automatic Answers? A User´s Based Study

Understanding the different ways of the information seeking behavior of users, and their implications is an important challenge of Web information services. In this paper we examine the suitability of Web search engines (SE) and community question-answering (community QA) to satisfy the different expectations of users: queries expecting knowledge-based answers, and queries expecting subjective opinion-based answers. From this categorization, we conducted a user study of the results obtained from three Web SE, and three communities QA. In this way, we found that SE result in a better alternative when the query is designed to get a uni-objective answer, while communities QA provide better results if the question gets multi-objective answers. On the other hand, when the query expects a subjective answer, none of these systems provides a very effective answer that can fulfill the expectations from the user. Knowing more about the type of queries that require human support would be useful to improve the user search experience in SE.