| SPECIAL SECTION:SOCIAL MEDIA PROCESSING |
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Image position and layout effects of multi-image tweets from the perspective of user engagement |
| MA Xiaoyue, MENG Xiao |
| School of Journalism and New Media, Xi'an Jiaotong University, Xi'an 710049, China |
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Abstract Inspired by user cognition research, this study explores the image position and layout effects on the transformation process from image content to user engagement behavior in multi-image tweets on the Sina Weibo platform. The XGBoost model trained on the single-image tweet data was used to predict each image's "user engagement potential" in multi-image tweets. Correlation analysis, Z-test, and ordinary least squares (OLS) regression analysis were used to verify the relationship between image position, layout, and user engagement. The results show that in multi-image tweets on the Sina Weibo platform, the image position and layout factors can affect user engagement behavior to a certain extent. That is, (1) for the image position effect, tweets containing 2, 4, 5, and 8 images had the right position effect. Tweets containing 6 and 8 images had the bottom position effect. Tweets containing 3 and 8 images had the edge and middle effects, respectively. Others, in most cases, had symmetric effects. (2) For the image layout effect, Layouts 2, 3, 4, 5, 6, and 8 can positively promote the user engagement potential transfer of images compared with the single image so that the image tweet may achieve user engagement beyond the average level of its potential. However, Layout 7 had a negative effect, and Layout 9 had no significant difference from single-image tweets. The results of this study can provide references for the release of social media image information.
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| Keywords
social media visualization
image distribution
user engagement
machine learning
regression analysis
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Issue Date: 14 January 2022
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Vol. 62
