Version 1
: Received: 14 August 2020 / Approved: 26 August 2020 / Online: 26 August 2020 (04:33:35 CEST)
How to cite:
Ahmed, S.; Rajput, A.E.; Sarirete, A.; Chawdhery, T.J. Social Media Platform: Measuring Readability and Socio-Economic Status. Preprints2020, 2020080560. https://doi.org/10.20944/preprints202008.0560.v1
Ahmed, S.; Rajput, A.E.; Sarirete, A.; Chawdhery, T.J. Social Media Platform: Measuring Readability and Socio-Economic Status. Preprints 2020, 2020080560. https://doi.org/10.20944/preprints202008.0560.v1
Ahmed, S.; Rajput, A.E.; Sarirete, A.; Chawdhery, T.J. Social Media Platform: Measuring Readability and Socio-Economic Status. Preprints2020, 2020080560. https://doi.org/10.20944/preprints202008.0560.v1
APA Style
Ahmed, S., Rajput, A.E., Sarirete, A., & Chawdhery, T.J. (2020). Social Media Platform: Measuring Readability and Socio-Economic Status. Preprints. https://doi.org/10.20944/preprints202008.0560.v1
Chicago/Turabian Style
Ahmed, S., Akila Sarirete and Tauseef J. Chawdhery. 2020 "Social Media Platform: Measuring Readability and Socio-Economic Status" Preprints. https://doi.org/10.20944/preprints202008.0560.v1
Abstract
Social media gives researchers an invaluable opportunity to gain insight into different facets of human life.Researchers put a great emphasis on categorizing the socioeconomic status (SES) of individuals to help predict various findings of interest. Forum uses, hashtags and so on are common tools of conversations grouping. On the other hand, crowdsourcing is a concept that involves gathering intelligence to group online user community based on common interest. This paper provides a mechanism to look at writings on social media and group them based on their academic background. We build upon earlier work where we analyzed online forum posts from various geographical regions in the USA and Canada and characterized the readability scores of such users. Specifically, we collected 1000 tweets from the members of the US Senate and computed the Flesch-Kincaid readability score for the Senators. Comparing the Senators’ tweets to the ones from average citizens, we note the following. 1) US Senators’ readability based on their tweets rate is much higher affirming the gap between the academic performance of US Senators and their average citizen, and 2) the immense difference among average citizen’s score compared to those of US Senators is attributed to the wide spectrum of academic attainment.
Keywords
Big Data; Natural Language Processing; Social media; Socioeconomic Status (SES); Social Computing
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
