Abstract
Goal contents pursuit reflects the motivational personality and can be an excellent indicator to predict individuals' life satisfaction and daily behaviors. However, due to the expense and subjective bias of questionnaires, it is challenging to obtain individual data and explore the effects of goal contents pursuit in conventional studies. Social media provides individuals with a communication context that can be used as a proxy to infer personality based on a massive of media footprints information. This study obtained 456 Weibo active users' self-reports of goal contents pursuit scale and their online behaviors that is established to train a competent machine learning model, which then successfully identifies the classification of intrinsic and extrinsic goals. From the perspective of Weibo users' features (i.e., basic, interactive, linguistic, and emotional features), the systematic comparison shows the significant differences in the pursuit level of intrinsic and extrinsic goals. This study advances the methodology of employing machine learning and online data to objectively delineate individual goal contents pursuit and paves the way to explore a massive number of individuals' personalities and behaviors.
Published Version
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