2013/04/06 by Shuguang Han, Zhen Yue, Han, Shuguang +3
Computer Science · Social Sciences · #Advanced Text Analysis Techniques #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Information Retrieval and Search Behavior #Misinformation and Its Impacts
paper · pdf · doi:10.48550/arxiv.1304.1924
openalex publication_date 2013/04/06 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Information seeking process is an important topic in information seeking behavior research. Both qualitative and empirical methods have been adopted in analyzing information seeking processes, with major focus on uncovering the latent search tactics behind user behaviors. Most of the existing works require defining search tactics in advance and coding data manually. Among the few works that can recognize search tactics automatically, they missed making sense of those tactics. In this paper, we proposed using an automatic technique, i.e. the Hidden Markov Model (HMM), to explicitly model the search tactics. HMM results show that the identified search tactics of individual information seeking behaviors are consistent with Marchioninis Information seeking process model. With the advantages of showing the connections between search tactics and search actions and the transitions among search tactics, we argue that HMM is a useful tool to investigate information seeking process, or at least it provides a feasible way to analyze large scale dataset.