User Engagement Data for Social Media (Experience and Behavior Dimensions)
Description
This dataset comprises two complementary sources of user engagement data collected to support the development and validation of the Experience–Behavior User Engagement Model for social media, as presented in the associated research article. The first component consists of self-reported questionnaire responses from 570 valid respondents collected via an online survey (Google Forms) during March 2025. Respondents were required to have followed or visited the Instagram account @tempo.co and to have viewed and responded to its content. The questionnaire measures four experiential dimensions adapted from the User Engagement Scale–Short Form (UES-SF): Aesthetics (AE), Perceived Usability (PU), Focused Attention (FA), and Reward (RW), using a 7-point Likert scale. The second component consists of social media engagement metrics scraped from Instagram Reels published by the @tempo.co account over the same one-month observation period (March 2025). For each post, the number of views, likes, and comments was recorded. Engagement rate variables (Like Rate and Comment Rate) were calculated as the ratio of interactions to exposures and transformed using an arcsine square root transformation to stabilize variance. Variables included in the dataset: respondent demographics (gender, age, domicile, education, occupation); questionnaire items for the AE, PU, FA, and RW dimensions; and engagement rate variables (Like Rate, Comment Rate). This dataset may be of interest to researchers studying social media engagement, user experience measurement, PLS-SEM methodology, and digital marketing analytics, particularly those examining the relationship between subjective user experience and observable behavioral outcomes on social media platforms.
Files
Steps to reproduce
Data collection and preparation followed the steps below: Questionnaire data collection: 1. A structured online questionnaire was developed by adapting items from the User Engagement Scale–Short Form (UES-SF), covering four dimensions: Aesthetics (AE), Perceived Usability (PU), Focused Attention (FA), and Reward (RW), measured on a 7-point Likert scale (1 = strongly disagree to 7 = strongly agree). Two additional items were included to support the Reward dimension in the social media context. 2. The questionnaire was distributed online via Google Forms to respondents who had followed or visited the Instagram account @tempo.co and had viewed and responded to its content (views, likes, and/or comments). 3. Data collection was conducted over one month (March 2025). 4. The total number of respondents with valid responses after screening was 570 respondents. Social media data collection: 5. Content data were scraped from the @tempo.co Instagram account over the same one-month period (March 2025) 6. For each post, the number of views, likes, and comments, along with the publication date, was recorded. Data processing and integration: 7. Reverse-scoring was applied to negatively worded questionnaire items to align their polarity with the remaining positively worded items. 8. Engagement rate variables were calculated for each post as the ratio of interactions to exposures: Like Rate = likes/views; Comment Rate = comments/views. 9. Transformed post-level engagement metrics were linked to individual questionnaire responses based on the date of survey completion, matching each respondent with the engagement metrics of the Instagram post(s) published on that date. 10. The final integrated dataset was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 3.0 to test models