Taking the pulse of US college campuses with location-based anonymous mobile apps

Yanqiu Wu, Tehila Minkus, Keithw Ross

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We deploy GPS hacking in conjunction with location-based mobile apps to passively survey users in targeted geographical regions. Specifically, we investigate surveying students at different college campuses with Yik Yak, an anonymous mobile app that is popular on US college campuses. In addition to being campus centric, Yik Yak's anonymity allows students to express themselves candidly without self-censorship. We collect nearly 1.6 million Yik Yak messages ("yaks") from a diverse set of 45 college campuses in the United States.We use natural language processing to determine the sentiment (positive, negative, or neutral) of all of the yaks. We employ supervised machine learning to predict the gender of the authors of the yaks and then analyze how sentiment differs among the two genders on college campuses.We also use supervised machine learning to classify all the yaks into nine topics and then investigate which topics are most popular throughout the US and how topic popularity varies on the different campuses. The results in this article provide significant insight into how campus culture and student's thinking varies among US colleges and universities.

    Original languageEnglish (US)
    Article number3078843
    JournalACM Transactions on Intelligent Systems and Technology
    Volume9
    Issue number1
    DOIs
    StatePublished - Sep 2017

    Keywords

    • Data mining
    • Social networks

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Artificial Intelligence

    Fingerprint Dive into the research topics of 'Taking the pulse of US college campuses with location-based anonymous mobile apps'. Together they form a unique fingerprint.

    Cite this