Popularity meter: An influence- and aesthetics-aware social media popularity predictor

Shintami Chusnul Hidayati, Yi Ling Chen, Chao Lung Yang, Kai Lung Hua

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Citations (Scopus)

Abstract

Social media websites have become an important channel for content sharing and communication between users on social networks. The shared images on the websites, even the ones from the same user, tend to receive a quite diverse distribution of views. This raises the problem of image popularity prediction on social media. To address this important research topic, we explore three essential components that have considerable impact of the image popularity, which are user profile, post metadata, and photo aesthetics. Moreover, we make use of state-of-the-art predictive modeling approaches to demonstrate the effectiveness of our proposed features in predicting image popularity. We then evaluate the proposed method through a large number of real image posts from Flickr. The experimental results show significant statistical evidence that incorporating the proposed features with ensemble learning method that combines predictions from support vector regression (SVR) and classification and regression tree (CART) models offers a satisfactory popularity prediction. By understanding the social behavior and the underlying structure of content popularity, our research results can also contribute to designing better algorithms for important applications like content recommendation and advertisement placement.

Original languageEnglish
Title of host publicationMM 2017 - Proceedings of the 2017 ACM Multimedia Conference
PublisherAssociation for Computing Machinery, Inc
Pages1918-1923
Number of pages6
ISBN (Electronic)9781450349062
DOIs
Publication statusPublished - 23 Oct 2017
Externally publishedYes
Event25th ACM International Conference on Multimedia, MM 2017 - Mountain View, United States
Duration: 23 Oct 201727 Oct 2017

Publication series

NameMM 2017 - Proceedings of the 2017 ACM Multimedia Conference

Conference

Conference25th ACM International Conference on Multimedia, MM 2017
Country/TerritoryUnited States
CityMountain View
Period23/10/1727/10/17

Keywords

  • Affective computing
  • Image popularity
  • Knowledge extraction
  • Popularity prediction
  • Social media

Fingerprint

Dive into the research topics of 'Popularity meter: An influence- and aesthetics-aware social media popularity predictor'. Together they form a unique fingerprint.

Cite this