Abstract
Abstract Social media contain abundant information about the events or news occurring all over the world. Social media growth has a greater impact on various domains like marketing, e-commerce, health care, e-governance, and politics, etc. Currently, Twitter was developed as one of the social media platforms, and now, it is one of the most popular social media platforms. There are 1 billion user’s profiles and millions of active users, who post tweets daily. In this research, buzz detection in social media was carried out by the semantic approach using the condensed nearest neighbor (SACNN). The Twitter and Tom’s Hardware data are stored in the UC Irvine Machine Learning Repository, and this dataset is used in this research for outlier detection. The min–max normalization technique is applied to the social media dataset, and additionally, missing values were replaced by the normalized value. The condensed nearest neighbor (CNN) is used for semantic analysis of the database, and based on the optimized value provided by the proposed method, the threshold is calculated. The threshold value is used to classify buzz and non-buzz discussions in the social media database. The result showed that the SACNN achieved 99% of accuracy, and relative error is less than the existing methods.
Highlights
The number users in social media are growing enormously and the information shared between them; the streaming of data posted on social media is increasing every day [18]
Twitter has many active users who are posting their own content related to the news or events
There are over millions of users in Twitter who create an enormous amount of data, which makes it difficult for buzz monitoring
Summary
The number users in social media are growing enormously and the information shared between them; the streaming of data posted on social media is increasing every day [18]. Hundreds of millions of users are contributing on social media and creating a huge volume of data in various blogs [4, 11]. The Microblog, a short form for mini blog, combines the social and information networks using the term of follower–friend relationship [7]. Twitter is one of the most popular social media tools, where people can send and read messages in the form of tweets. Twitter has 316 million monthly active users, and 500 million tweets are sent every day [15]. The users have the liberty to tweet about anything from their mind; for instance, tweets that are related to quotes, lyrics, ideas, news stories, etc., can be sent in Twitter. The users can tweet their message within 140 characters, and the corresponding followers can instantly get the tweets of the users [16]
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