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Multimodal Context-Aware Recommender for Post Popularity Prediction in Social Media

Published: 23 October 2017 Publication History

Abstract

Millions of multimodal posts are uploaded, shared, viewed and liked every day in different social networks, where users express their opinions about different items such as products and places. While, some user posts become popular, others are ignored. Even different posts related to the same items shared by different users receive different number of likes and views. Existing research on popularity prediction aggregate all user posts related to different items without considering the preferences of individual user for the items in training a popularity model. This often results in limited success. We hypothesize that popularity of posts differs from one user to the other user, one item to the other items, and posts related to the similar users or similar items may be received the same number of likes. In this paper, we present an approach for predicting the popularity of user posts by considering preferences of individual users to the items. We factorize the popularity of posts to the user-item-context and propose a multimodal context-aware recommender for predicting the popularity of posts. Using our proposal we have the ability of predicting the popularity of posts related to different items which are shared by a specific user. Moreover we are able to predict the popularity of posts shared with different users for a specific item. We evaluate our approach on an Instagram user posts dataset with over 600K posts in total related to different touristic places, as items, in The Netherlands for the task of popularity prediction.

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  • (2024)Semantics-enriched spatiotemporal mapping of public risk perceptions for cultural heritage during radical eventsInternational Journal of Disaster Risk Reduction10.1016/j.ijdrr.2024.104857(104857)Online publication date: Sep-2024
  • (2023)Complementary Model Fusion for Enhanced Social Popularity Prediction2023 International Conference on Computer and Applications (ICCA)10.1109/ICCA59364.2023.10401547(1-7)Online publication date: 28-Nov-2023
  • (2022)Are High-quality Photos More Popular Than Low-quality Ones? A Quantitative Study2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP55362.2022.9948731(1-5)Online publication date: 26-Sep-2022
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cover image ACM Conferences
Thematic Workshops '17: Proceedings of the on Thematic Workshops of ACM Multimedia 2017
October 2017
558 pages
ISBN:9781450354165
DOI:10.1145/3126686
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 October 2017

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Author Tags

  1. multimedia analysis
  2. popularity prediction
  3. recommender system

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  • Research-article

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  • Amsterdam Data Science

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MM '17
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MM '17: ACM Multimedia Conference
October 23 - 27, 2017
California, Mountain View, USA

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Cited By

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  • (2024)Semantics-enriched spatiotemporal mapping of public risk perceptions for cultural heritage during radical eventsInternational Journal of Disaster Risk Reduction10.1016/j.ijdrr.2024.104857(104857)Online publication date: Sep-2024
  • (2023)Complementary Model Fusion for Enhanced Social Popularity Prediction2023 International Conference on Computer and Applications (ICCA)10.1109/ICCA59364.2023.10401547(1-7)Online publication date: 28-Nov-2023
  • (2022)Are High-quality Photos More Popular Than Low-quality Ones? A Quantitative Study2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP55362.2022.9948731(1-5)Online publication date: 26-Sep-2022
  • (2022)Image Popularity Prediction Over Time For the Span Of 30 Days Using Machine learning Techniques2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)10.1109/ICoDT255437.2022.9787438(1-7)Online publication date: 24-May-2022
  • (2022)A Survey On Prevalent Approaches To Predict The Popularity Of Social Content2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)10.1109/ICoDT255437.2022.9787430(1-7)Online publication date: 24-May-2022
  • (2021)Predicting Implicit User Preferences with Multimodal Feature Fusion for Similar User Recommendation in Social MediaApplied Sciences10.3390/app1103106411:3(1064)Online publication date: 25-Jan-2021
  • (2021)Comparative study of recommender system approaches and movie recommendation using collaborative filteringInternational Journal of System Assurance Engineering and Management10.1007/s13198-021-01087-xOnline publication date: 19-Apr-2021
  • (2019)Social Media Popularity PredictionProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3356062(2682-2686)Online publication date: 15-Oct-2019
  • (2018)Random Forest Exploiting Post-related and User-related Features for Social Media Popularity PredictionProceedings of the 26th ACM international conference on Multimedia10.1145/3240508.3266439(2013-2017)Online publication date: 15-Oct-2018
  • (2018)Popularity prediction of images and videos on Instagram2018 4th International Conference on Web Research (ICWR)10.1109/ICWR.2018.8387246(111-117)Online publication date: Apr-2018
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