Predicting Virality of Tweets Using ML Algorithms and Analyzing Key Determinants of Viral Tweets

被引:0
|
作者
Arunkumar, Preeti [1 ]
Jadhav, Anil [1 ]
机构
[1] Symbiosis Int Deemed Univ, Symbiosis Ctr Informat Technol, Pune, Maharashtra, India
来源
ARTIFICIAL INTELLIGENCE: THEORY AND APPLICATIONS, VOL 1, AITA 2023 | 2024年 / 843卷
关键词
Machine learning; Virality; Social media; Twitter; INTELLIGENCE; POPULARITY;
D O I
10.1007/978-981-99-8476-3_13
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Social media is no longer just a medium for socialization but has become a medium for business. There has been an exponential growth of user-generated content in both volume and significance. Researchers have studied the behavioral side of social media, reviews, and social network communities. Some researchers have analyzed tweets and found that only the content with strong negative emotions gets retweeted. There is a lack of research focusing on other factors like the length of a tweet, user's follower counts, etc., affecting the success of a tweet. Advancements in technology help us to use machine learning algorithms to predict if the post will go viral or not. This research paper also finds and verifies the key determinants that contribute to a tweet's success. This paper also concludes with the most appropriate machine learning model for predicting the Virality of a tweet.
引用
收藏
页码:155 / 165
页数:11
相关论文
共 32 条
  • [31] Analyzing the effects of streetscape and land use on urban accidents and predicting future accidents by using machine learning algorithms (case study: Mashhad)
    Bagheri, Seyed Amir Mohammad
    Mojaradi, Barat
    Kamboozia, Neda
    Faizi, Mohsen
    HELIYON, 2024, 10 (13)
  • [32] Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa
    Yehuala, Tirualem Zeleke
    Mengesha, Sara Beyene
    Baykemagn, Nebebe Demis
    FRONTIERS IN GLOBAL WOMENS HEALTH, 2025, 6