Finding user personal interests by tweet-mining using advanced machine learning algorithm in R

14th International Conference on Science, Engineering and Technology

自然科学;工业技术

Krithika, L.B.^1 ; Roy, P.^1 ; Asha Jerlin, M.^1

School of Information Technology and Engineering, VIT University, Vellore

Tamil Nadu

632014, India^1

关键词: Social annotations;    Social media;    State-of-the-art techniques;    Topic model;    Traditional techniques;    Tweet minings;    Twitter social networks;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/263/4/042071/pdf
DOI  :  10.1088/1757-899X/263/4/042071

来源: IOP

【 摘 要 】

The social-media plays a key role in every individual's life by anyone's personal views about their liking-ness/disliking-ness. This methodology is a sharp departure from the traditional techniques of inferring interests of a user from the tweets that he/she posts or receives. It is showed that the topics of interest inferred by the proposed methodology are far superior than the topics extracted by state-of-the-art techniques such as using topic models (Labelled LDA) on tweets. Based upon the proposed methodology, a system has been built, "Who is interested in what", which can infer the interests of millions of Twitter users. A novel mechanism is proposed to infer topics of interest of individual users in the twitter social network. It has been observed that in twitter, a user generally follows experts on various topics of his/her interest in order to acquire information on those topics. A methodology based on social annotations is used to first deduce the topical expertise of popular twitter users and then transitively infer the interests of the users who follow them.