{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T03:58:26Z","timestamp":1780372706917,"version":"3.54.1"},"reference-count":64,"publisher":"MIS Quarterly","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,6,1]]},"abstract":"<jats:p>Theories of personal branding are built on the idea that each individual should be aware of the persona they present to the world. Nowadays, as social interactions are increasingly shifting to the online arena, users of social platforms are presented with many new opportunities and technology-enabled tools by which they can construct their online personas. A powerful type of tool that has emerged in this ecosystem is the ability to reiterate a friend\u2019s activity, that is, to redistribute an exact copy of the content that the friend has posted online (e.g., words, videos, or pictures) and to incorporate it into one\u2019s own online image. In this work, we examine how users employ reiteration tools when presenting themselves and shaping their online presence. We focus on retweeting behavior on Twitter and study the spectrum of topics that users choose to reiterate. We hypothesize that users\u2019 retweeting behavior will show patterns that are theorized to characterize effective personal branding strategies: Specifically, when reiterating content produced by others, a user will maintain a persona that is consistent with the persona portrayed in self-produced tweets.<\/jats:p>\n               <jats:p>We analyze data taken from Twitter over a period of 6 months in 2016, with regard to 3,388 nonexpert users and 464 expert users and the users whom they followed. We use LDA topic modeling to derive the topics in each user\u2019s self-produced tweets and retweets. We find that users\u2019 retweets tend to focus on the topics they address in their self-produced tweets, instead of adding new topics. Further, we find that a user\u2019s retweets do remarkably little to alter the distribution of topics discussed in self-produced tweets. Finally, we find that this tendency is more prominent among \u201cexpert\u201d users (i.e., professional bloggers who are particularly likely to use Twitter as a personal branding tool). A rigorous identification strategy lends support to the proposition that the observed effects are indeed driven by image-related considerations rather than by alternative factors known to influence retweeting behavior, such as exposure bias (a phenomenon associated with the formation of echo chambers), need for uniqueness, and social dynamics on the Twitter platform.<\/jats:p>","DOI":"10.25300\/misq\/2019\/14346","type":"journal-article","created":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T12:07:42Z","timestamp":1559218062000},"page":"501-524","source":"Crossref","is-referenced-by-count":72,"title":["Using Retweets When Shaping Our Online Persona: Topic Modeling Approach1"],"prefix":"10.25300","volume":"43","author":[{"given":"Hilah","family":"Geva","sequence":"first","affiliation":[{"name":"The Coller School of Management, Tel-Aviv University, Tel Aviv, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gal","family":"Oestreicher-Singer","sequence":"additional","affiliation":[{"name":"The Coller School of Management, Tel-Aviv University, Tel Aviv, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maytal","family":"Saar-Tsechansky","sequence":"additional","affiliation":[{"name":"McCombs School of Business, University of Texas at Austin, Austin, TX 79712 U.S.A."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10933","published-online":{"date-parts":[[2019,6,1]]},"reference":[{"key":"2025082212121351700_b1-07_14346_ra_gevaoestreicher","first-page":"21544","article-title":"Distinguishing Influence-Based Contagion from Homophily-Driven Diffusion in Dynamic Networks","author":"Aral","year":"2009"},{"key":"2025082212121351700_b2-07_14346_ra_gevaoestreicher","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/978-3-642-13657-3_43","article-title":"On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"Arun","year":"2010"},{"key":"2025082212121351700_b3-07_14346_ra_gevaoestreicher","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1177\/0956797609360756","article-title":"Facebook Profiles Reflect Actual Personality, Not Self-Idealization","volume":"21","author":"Back","year":"2010","journal-title":"Psychological Science"},{"issue":"6239","key":"2025082212121351700_b4-07_14346_ra_gevaoestreicher","doi-asserted-by":"crossref","first-page":"1130","DOI":"10.1126\/science.aaa1160","article-title":"Exposure to Ideologically Diverse News and Opinion on Facebook","volume":"348","author":"Bakshy","year":"2015","journal-title":"Science"},{"issue":"8","key":"2025082212121351700_b5-07_14346_ra_gevaoestreicher","doi-asserted-by":"crossref","first-page":"1902","DOI":"10.1287\/mnsc.2014.2081","article-title":"Do Your Online Friends Make You Pay? 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