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West Ashley Library
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Wando Mount Pleasant Library
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Hurd/St. Andrews Library
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Socioeconomic Patterns of Twitter User Activity.
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- Author(s): Abitbol, Jacob Levy; Morales, Alfredo J.
- Source:
Entropy; Jun2021, Vol. 23 Issue 6, p780-780, 1p- Subject Terms:
- Source:
- Additional Information
- Abstract: Stratifying behaviors based on demographics and socioeconomic status is crucial for political and economic planning. Traditional methods to gather income and demographic information, like national censuses, require costly large-scale surveys both in terms of the financial and the organizational resources needed for their successful collection. In this study, we use data from social media to expose how behavioral patterns in different socioeconomic groups can be used to infer an individual's income. In particular, we look at the way people explore cities and use topics of conversation online as a means of inferring individual socioeconomic status. Privacy is preserved by using anonymized data, and abstracting human mobility and online conversation topics as aggregated high-dimensional vectors. We show that mobility and hashtag activity are good predictors of income and that the highest and lowest socioeconomic quantiles have the most differentiated behavior across groups. [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Entropy is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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