Predicting comments on Facebook photos: Who posts might matter more than what type of photo is posted

Abstract

The number of likes and comments received to social media posts and images are influential for users’ self-presentation and problematic Facebook use. The aim of this study was to highlight the most relevant factors predicting the popularity (i.e., the probability to receive at a least a comment) of Facebook photos based on: (i) Facebook user-related features; (ii) Facebook photo-related features; and (iii) and psychological variables. A mixed approach was used, including objective data extracted from Facebook (regarding users’ characteristics and photo features) as well as answers to a questionnaire. Participants were 227 Facebook users (M = 25.01(1.05) years). They were asked to answer a questionnaire and provide a copy of their Facebook profile data. A total of 180,547 photos receiving a total of 122,689 comments were extracted. Results showed that user-related features (Facebook network and activities) were the most relevant in predicting image popularity accurately. It seems that who posts a Facebook photo matters more than the type of photo posted and the psychological profile of the user. Results are discussed within a psychological perspective.Future research should look at the sentiment (positive vs. negative) of the comments received by different types of photos. This is the first study exploring what makes a Facebook photo popular using objective data rather than self-reported frequency of Facebook activity only. Results might advance current methods and knowledge about potential problematic behaviors on social media.

Keywords

• Facebook
• Photo
• Objective data
• Comment
• Machine learning