A hybrid MCDM model combining DANP with TODIM to evaluate the information quality of community question answering in a two‐dimensional linguistic environment

Abstract

Evaluating the information quality of cQA (community question‐answering) websites helps users select a cQA website with high‐quality information and improves the information quality. In this paper, an approach to evaluating the information quality of cQA based on a novel hybrid multicriteria decision‐making (MCDM) model is proposed. First, the source, content, expression and usefulness criteria for evaluating the information quality of the cQA are established. Then, considering the ambiguity and inner correlations of the criteria, DANP ([DEMATEL]‐based Analytic Network Process) and TODIM (interactive and multiple attribute decision making, in Portuguese) methods are combined in a two‐dimensional linguistic environment to process linguistic evaluation information. Lastly, the proposed approach is applied to evaluate the quality of five popular cQA websites. The key criteria are identified, and the evaluation results are derived comprehensively. The key factors consist of reputation, coverage, politeness, usability, helpfulness, clarity, readability and conciseness. The websites, Know almost and Baidu knows, perform better in terms of information quality. The application, along with the sensitivity analysis and comparative analysis, shows the effectiveness of the proposed model. The proposed approach has both practical and research implications. It provides an approach for users to choose websites, and, for operators, to improve the information quality of their website. The evaluation criteria and their relations provide a reference for research on the information quality. The evaluation method considers the user's psychological information to provide a more accurate MCDM approach. The comprehensive aspects of the experiment can be used to verify the other MCDM methods.

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