2022 Research in the Capitol

Location

Iowa State House, Rotunda

Presentation Type

Open Access Poster Presentation

Abstract

Loneliness, isolation, and anti-social behaviors have increased in the past few years, whether that be due to social media, people paying more attention to their devices, or due to the COVID-19 pandemic. These behaviors are proven to decrease a student’s academic performance, causing their grades to decline, and disabling their motivation to learn. We aim to gain insight on this issue via the application of smartphone technology and machine learning, enabling those that use our app to understand if their being social or anti-social. We use a variety of sensors, location devices, and speaker recognition algorithms to identify behaviors that help us let the user know when they’re being negatively affected by their social behavior. Our end goal is to be able to tell students and users a “social score” after an interval of time, helping them identify and fix when they’re being overly isolated or lonely.

Start Date

21-2-2022 11:30 AM

End Date

21-2-2022 1:30 PM

Event Host

University Honors Programs, Iowa Regent Universities

Faculty Advisor

Dheryta Jaisinghani

Department

Department of Computer Science

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

File Format

application/pdf

Available for download on Wednesday, March 01, 2023

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Feb 21st, 11:30 AM Feb 21st, 1:30 PM

SocioApp: Detecting Your Sociability Status with Your Smartphone

Iowa State House, Rotunda

Loneliness, isolation, and anti-social behaviors have increased in the past few years, whether that be due to social media, people paying more attention to their devices, or due to the COVID-19 pandemic. These behaviors are proven to decrease a student’s academic performance, causing their grades to decline, and disabling their motivation to learn. We aim to gain insight on this issue via the application of smartphone technology and machine learning, enabling those that use our app to understand if their being social or anti-social. We use a variety of sensors, location devices, and speaker recognition algorithms to identify behaviors that help us let the user know when they’re being negatively affected by their social behavior. Our end goal is to be able to tell students and users a “social score” after an interval of time, helping them identify and fix when they’re being overly isolated or lonely.