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首页> 外文期刊>Journal of management information systems >Classifying, Measuring, and Predicting Users' Overall Active Behavior on Social Networking Sites
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Classifying, Measuring, and Predicting Users' Overall Active Behavior on Social Networking Sites

机译：在社交网站上对用户的总体积极行为进行分类，评估和预测

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摘要

Although understanding the role of users' overall active behavior on a social networking site (SNS) is of significant importance for both theory and practice, the complexity and difficulty involved in measuring such behavior has inhibited research attention. To understand users' active behaviors on an SNS, it is important that we identify and classify various types of online behaviors before measuring them. In this paper we holistically examine users' active behaviors on an SNS. Toward this end, we conduct three studies. First, we classify active behaviors on an SNS into four categories using the Delphi method. Then, we develop a measurement model and validate it using the data collected from an online survey of 477 SNS users. The measures of the developed instrument exhibit satisfactory reliability and validity and are used as indicators of the latent constructs. This instrument is then used in a predictive model based on commitment theory and tested using data from 1,242 responses. The results of data analysis suggest that affective commitment and continuance commitment are good predictors of overall active behavior on an SNS. This study complements the existing research on social media, cocreation, and social commerce. Most important, this study provides a theoretically sound measurement instrument that addresses the complex characteristic of overall active behavior on an SNS and which should be useful for future research. The findings of this study have important implications for practice as they highlight managing and stimulating users' active behaviors on an SNS.
机译：尽管了解用户在社交网站（SNS）上的总体积极行为的作用对于理论和实践都具有重要意义，但是衡量此类行为的复杂性和难度却抑制了研究的注意力。为了了解用户在SNS上的活跃行为，重要的是我们在测量各种行为之前先对其进行识别和分类。在本文中，我们全面地研究了用户在SNS上的活跃行为。为此，我们进行了三项研究。首先，我们使用Delphi方法将SNS上的活跃行为分为四类。然后，我们开发一个测量模型，并使用从477个SNS用户的在线调查中收集的数据进行验证。所开发仪器的测量结果显示出令人满意的可靠性和有效性，并被用作潜在构造的指标。然后将该工具用于基于承诺理论的预测模型中，并使用来自1,242个响应的数据进行测试。数据分析的结果表明，情感承诺和持续承诺是SNS整体积极行为的良好预测指标。该研究是对现有社交媒体，联合娱乐和社交商务研究的补充。最重要的是，这项研究提供了一种理论上合理的测量工具，可以解决SNS上整体主动行为的复杂特征，这对将来的研究应是有用的。这项研究的发现对实践具有重要意义，因为它们强调了在SNS上管理和激发用户的积极行为。

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