Computerized emotional content analysis: empirical findings based on charity social media advertisements

Abstract

There has been a long debate about effective emotional appeals on charity advertisements. While many charity organizations recently shifted from negative emotions to happy emotions on their social media, it is not clearly proven whether this strategy is more effective. The objective of this study is to find more detailed unknown information to optimally use emotional charity advertisements on social media. We investigate the effect of 1) emotional valence, 2) their match between images and textual descriptions, 3) their length, and 4) their post timing on social media engagement. By automatically extracting emotions expressed both in facial images and textual descriptions from 3,066 charity posts from Save the Children’s official Instagram account using the computerized emotional content analysis, we provide findings on what, how much, when, and how charity managers can come up with a clear configuration for their social media advertisements.

Keywords:

• Charity emotion advertisement
• social media
• multi-modal content analysis
• computerized automatic emotional content analysis
• emotional valence
• emotional match
• text length by emotional type
• post timing

Disclosure statement

The authors declare that there is no conflict of interest.

Funding

This research received no external funding.

Notes

1 We acquired permission from Save the Children to use the above pictures in this paper.