Reimagining Current Messaging Systems of Social Networks – UROP Spring Symposium 2021

Reimagining Current Messaging Systems of Social Networks

Jolie Kaplan

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Pronouns: she/her

Research Mentor(s): Eric Gilbert, John Derby Evans Associate Professor
Research Mentor School/College/Department: School of Information,
Presentation Date: Thursday, April 22, 2021
Session: Session 1 (10am-10:50am)
Breakout Room: Room 18
Presenter: 2

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Abstract

While social networks have enabled improved communication globally and the widespread Human-Computer Interaction (HCI), it has also exasperated unsolicited communication and harassing messages which consistently target vulnerable, marginalized groups. Consentful Messaging offers Twitter users the ability to filter potential message senders before the risk of receiving unsolicited messages through a system built on Twitter’s API, Python, and JavaScript. The field deployment of Consentful Messaging will reveal how social media users choose to receive messages and to what extent they wish to customize potential message senders. Consentful Messaging is made of four possible customizable functions: the user can set a threshold of number of followers required for a potential message sender, the Consentful Messaging user can verify whether they follow the potential message sender, the Consentful Messaging user can determine whether the potential message sender is followed by at least one account that the Consentful Messaging user follows, and verify whether the Consentful Messaging user has ever replied to a message from the potential message sender. The result is that Consentful Messaging Twitter extension will be deployed in March of 2021. This field study will show how and to what extent Twitter users choose to protect themselves from unsolicited messages with the help of technology. Consentful Messaging will offer not only a customizable layer of protection to marginalized social media users by providing a board for healthy interactions among users, but also information as to how Twitter users interact with and modify personalized computer settings.

Authors: Jolie Kaplan
Research Method: Computer Programming

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