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A Data-Driven Expectation Prediction Framework Based on Social Exchange Theory
<span title="2022-01-10">2022</span>
<i title="Frontiers Media SA">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5r5ojcju2repjbmmjeu5oyawti" style="color: black;">Frontiers in Psychology</a>
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Along with the rapid application of new information technologies, the data-driven era is coming, and online consumption platforms are booming. However, massive user data have not been fully developed for design value, and the application of data-driven methods of requirement engineering needs to be further expanded. This study proposes a data-driven expectation prediction framework based on social exchange theory, which analyzes user expectations in the consumption process, and predicts
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fpsyg.2021.783116">doi:10.3389/fpsyg.2021.783116</a>
<a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35082724">pmid:35082724</a>
<a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8784405/">pmcid:PMC8784405</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2abgffp5lnhltb44uep4udfrai">fatcat:2abgffp5lnhltb44uep4udfrai</a>
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... ent plans to assist designers make better design improvement. According to the classification and concept definition of social exchange resources, consumption exchange elements were divided into seven categories: money, commodity, services, information, value, emotion, and status, and based on these categories, two data-driven methods, namely, word frequency statistics and scale surveys, were combined to analyze user-generated data. Then, a mathematical expectation formula was used to expand user expectation prediction. Moreover, by calculating mathematical expectation, explicit and implicit expectations are distinguished to derive a reliable design improvement plan. To validate its feasibility and advantages, an illustrative example of CoCo Fresh Tea & Juice service system improvement design is further adopted. As an exploratory study, it is hoped that this study provides useful insights into the data mining process of consumption comment.
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