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Correlation Analysis of Internet Addiction with Daily Behavior: A Data-Driven Method

Published: 23 October 2020 Publication History

Abstract

Internet addiction refers to excessive Internet use in daily life. Its negative impact on college students calls for timely discovery of its reasons and correct guidance. However, present research methods are mainly based on the questionnaire, which can be affected by non-randomly selected samples and a low response rate. Thanks to the development of the smart campus, students' behavior can be recorded as data, thus whether Internet addiction is correlated with daily behavior can be analyzed quantitatively. In this paper, we extracted five features and proposed an Internet Addiction Rating Scale (IARS) to quantify students' Internet addiction level based on the Internet login data, and found that Internet addiction is positively correlated with consumption amount, negatively correlated with consumption speed and academic performance, but has little relationship with self-discipline. Our work throws some light on the relationship between students' Internet addiction and daily behavior through unobtrusive data analysis, helping college management staff detect abnormal learning status timely and reasonably.

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Cited By

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  • (2022)Review of Persuasive User Interface as Strategy for Technology Addiction in Virtual Environments2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct57072.2022.00019(44-54)Online publication date: Oct-2022

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  1. Correlation Analysis of Internet Addiction with Daily Behavior: A Data-Driven Method

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    ICBDT '20: Proceedings of the 3rd International Conference on Big Data Technologies
    September 2020
    250 pages
    ISBN:9781450387859
    DOI:10.1145/3422713
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 23 October 2020

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    Author Tags

    1. Campus Data Mining
    2. Correlation Analysis
    3. Internet Addiction

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    • Office of Leading Group of Jilin Province for Educational Science Research

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    • (2022)Review of Persuasive User Interface as Strategy for Technology Addiction in Virtual Environments2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct57072.2022.00019(44-54)Online publication date: Oct-2022

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