Predicting Emerging Trends on Social Media by Modeling it as Temporal Bipartite Networks (original) (raw)

IRJET- A Sequential Prediction Model for Topic Popularity in Social Media Networks

IRJET, 2020

It is extremely popular to identify trendy topics, which can profit numerous assignments including topic prediction, the direction of popular sentiments, for future precaution in upcoming problems, etc. However, at point, peoples might need to know when to make a topic popular. In this paper, we address this issue by presenting a Sequential Prediction Model for User Topic Selection (UTS) which models clients' practices of posting messages and comments. The UTS model considers clients' interests, companion circles, and startling occasions in online interpersonal organizations. Likewise, it considers the continual fleeting displaying of points, since themes are changing constantly after some time. Besides, a weighting plan is proposed to alterations in the changes of topic popularity. At long last, the trial prediction comes about on true informational collections and generates the prediction graph based on the user's thoughts and interests which will reveal the success of our proposed models, and point topic popularity prediction.

Prediction of Popular Content from Social Media Mining

2015

In recent trends social media websites, such as Facebook, Twitter, LinkedIn, YouTube and Google+ having certain content will attract much more visitors than others. Predicting the popularity of web content has become an active area of research. Predicting which content will become popular is of interest to website owners and market analysts. Popularity of content in social media is unequally distributed, with some items receiving a more attention from users. In Business analysis which newly submitted items will become popular is critically important for both companies that host social media sites and their users. Understanding what makes one item more popular than another, observing its popularity dynamics and being able to predict its popularity has thus attracted a lot of interest in the past few years. Predicting the popularity of web content is useful in many areas such as network dimensioning, online marketing or real-world outcome prediction. In this review, review of the curr...