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Date

22. 1.2021 14:20:27

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Abstract

This study investigates the content of questions and responses about the Zika virus on Yahoo! Answers as a recent example of how public concerns regarding an international health issue are reflected in social media. We investigate the contents of posts about the Zika virus on Yahoo! Answers, identify and reveal subject patterns about the Zika virus, and analyze the temporal changes of the revealed subject topics over 4 defined periods of the Zika virus outbreak. Multidimensional scaling analysis, temporal analysis, and inferential statistical analysis approaches were used in the study. A resulting 2-layer Zika virus schema, and term connections and relationships are presented. The results indicate that consumers' concerns changed over the 4 defined periods. Consumers paid more attention to the basic information about the Zika virus, and the prevention and protection from the Zika virus at the beginning of the outbreak of the Zika virus. During the later periods, consumers became more interested in the role that the government and health organizations played in the public health emergency.

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Abstract

This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users' privacy protection, i.e., it is required to comprehensively improve the security of users' preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.