Differences in Personal and Professional Tweets of Scholars

TL;DR

This study investigates differences in how university professors use Twitter for personal and professional purposes, analyzing affordances and framing behaviors to aid altmetric research and tweet interpretation.

Contribution

It introduces a socio-technical framework and a novel Mechanical Turk method for categorizing tweets, highlighting differences in affordance use and framing behaviors.

Findings

Significant differences in Twitter account types and affordance use.

Distinct framing behaviors in personal versus professional tweets.

Mechanical Turk effectively categorizes tweets for altmetric analysis.

Abstract

Purpose: This study shows that there were differences in the use of Twitter by professors at universities in the Association of American Universities (AAU). Affordance use differed between the personal and professional tweets of professors. Framing behaviors were described that could impact the interpretation of tweets by audience members. Design/methodology/approach: A three phase research design was used that included surveys of professors, categorization of tweets by Amazon's Mechanical Turk workers (i.e., turkers), and categorization of tweets by active professors on Twitter. Findings: There were significant differences found between professors that reported having a Twitter account, significant differences found between types of Twitter accounts (personal, professional, or both), and significant differences in the affordances used in personal and professional tweets. Framing behaviors were described that may assist altmetric researchers in distinguishing between personal and professional tweets. Research limitations/implications (if applicable): The study is limited by the sample population, survey instrument, low survey response rate, and low Cohen's kappa. Practical implications (if applicable): An overview of various affordances found in Twitter is provided and a novel use of Amazon's Mechanical Turk for the categorization of tweets is described that can be applied to future altmetric studies. Originality/value: This work utilizes a socio-technical framework integrating social and psychological theories to interpret results from the tweeting behavior of professors and the interpretation of tweets by workers in Amazon's Mechanical Turk.