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2021 | OriginalPaper | Chapter

Analyzing App-Based Methods for Internet De-Addiction in Young Population

Authors : Lakshita Sharma, Prachi Hooda, Raghav Bansal, Shivam Garg, Swati Aggarwal

Published in: Applications of Artificial Intelligence and Machine Learning

Publisher: Springer Singapore

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Abstract

With recent advancements in technology and the excessive use of smartphones, all internet-based applications like WhatsApp, Facebook, Netflix, etc. are one tap away, thereby resulting in increased internet usage on an average, especially among the young population. This has affected the cognitive and affective processes of the users and has caused various problems like loss of focus, fatigue, and burning sensations in the eyes, severe harm to mental health, reduction in response to events happening around, and many more. An unconventional method of recovering from internet addiction could be the use of mobile applications that help users monitor their usage and motivate them to have better self-control. There are a number of such applications, henceforth called apps, available that claim to help recover from internet addiction. However, their efficacy in curbing internet use has not been studied previously. This study is primarily based on assessing the efficiency of these app-based recovery methods from internet addiction. Using statistical analysis and polynomial regression, it was found that these apps do help in lowering internet use. This effect is largely seen in the first week of app use, after which significant reduction is not observed.

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Metadata
Title
Analyzing App-Based Methods for Internet De-Addiction in Young Population
Authors
Lakshita Sharma
Prachi Hooda
Raghav Bansal
Shivam Garg
Swati Aggarwal
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-16-3067-5_17

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