Collecting data of SNS user behavior to detect symptoms of excessive usage: Development of data collection application

Conference proceedings article

Authors/Editors

TIRANEE ACHALAKUL

Strategic Research Themes

No matching items found.

Publication Details

Author list: Intapong P., Achalakul T., Ohkura M.

Publisher: Springer

Publication year: 2017

Volume number: 486

Start page: 89

End page: 99

Number of pages: 11

ISBN: 9783319416847

ISSN: 2194-5357

eISSN: 2194-5357

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992645537&doi=10.1007%2f978-3-319-41685-4_9&partnerID=40&md5=4cf9fee488525301531ee2d9b11b6472

Languages: English-Great Britain (EN-GB)

View on publisher site

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. ฉ Springer International Publishing Switzerland 2017.

Keywords