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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Collecting Data of SNS User Behavior to Detect Symptoms of Excessive Usage: Development of Data Collection Application
verfasst von : Ploypailin Intapong, Tiranee Achalakul, Michiko Ohkura
Erschienen in: Advances in Ergonomics Modeling, Usability & Special Populations
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Abstract
Worldwide use of social networking sites (SNSs) continues to dramatically increase. People are spending unexpected and unprecedented amounts of time online. However, many studies have warned about the negative consequences of excessive SNS usage, including the potential of addictive behavior. Therefore, detecting the symptoms of excessive SNS usage is necessary. Data collection is an important first step for analyzing the usage behavior of SNSs. This article describes the development of a data collection application. We employed questionnaires to gather user experiences of SNS and APIs to retrieve SNS data by focusing on Twitter and Facebook. Unfortunately, these methods are limited. Self-report data might be inaccurate. Also, some data on SNSs might not be collectable by APIs. Thus, we will collect more data from internet service providers (ISPs). The obtained data from our application will be applied to detect the symptoms of excessive use of SNSs and develop prevention strategies.