文章基本信息

标题：Popularity Prediction of Instagram Posts
本地全文：下载
作者：Salvatore Carta ; Alessandro Sebastian Podda ; Diego Reforgiato Recupero 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2020
卷号：11
期号：9
页码：453-469
DOI：10.3390/info11090453
出版社：MDPI Publishing
摘要：Predicting the popularity of posts on social networks has taken on significant importance in recent years, and several social media management tools now offer solutions to improve and optimize the quality of published content and to enhance the attractiveness of companies and organizations. Scientific research has recently moved in this direction, with the aim of exploiting advanced techniques such as machine learning, deep learning, natural language processing, etc., to support such tools. In light of the above, in this work we aim to address the challenge of predicting the popularity of a future post on Instagram, by defining the problem as a classification task and by proposing an original approach based on Gradient Boosting and feature engineering, which led us to promising experimental results. The proposed approach exploits big data technologies for scalability and efficiency, and it is general enough to be applied to other social media as well.
关键词：popularity prediction; classification; social network; machine learning; instagram popularity prediction ; classification ; social network ; machine learning ; instagram