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Abstract
With the development of online commentary research, scholars have tried to tap into the deeper value of online commentary from the analysis of sentiment analysis, quality evaluation, false comment recognition to the usefulness of comments. Previous studies have focused on online product reviews while news reviews. Social media research has been relatively rare. social media and news commentary contain readers' opinions and evaluations on current events, and reflect the trend of public opinion. The purpose of this paper is to investigate and analyze the intrinsic link between social media content of different type and the number of commentaries, and sentiment analysis.
Highlights
There are many social networks in use today, like Facebook, Twitter, YouTube, and many others
We aim to investigate the underlying reasons of people leaving their comments on different channels of videos
H1, Whether the categories of videos affect the number of comments on social media? H2, Whether the viewer’s comments directly related to the videos content?. (This paper extracts text features, sentiment features, data analysis from different type videos reviews according to relevant research, formulates an evaluation system for video review and video categories popularity prediction task.)
Summary
There are many social networks in use today, like Facebook, Twitter, YouTube, and many others. Social media has been broadly used in the recommender system, sentiment analysis, text mining, business approach and marketing. A key aspect of social networks is richer in information that brings the challenges and opportunities in the data mining and knowledge discovery. There makes it appear that many researchers have started to study online reviews and have already made good progress. Most social media researches focused on excavating the emotional factors contained in commentary, evaluating the quality of different content commentary
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