Classification of Sina Web popularity topics based on LDA model

ZhengPu Yue

doi:10.1117/12.3036522

16 August 2024 Classification of Sina Web popularity topics based on LDA model

ZhengPu Yue

Author Affiliations +

Proceedings Volume 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024); 132300O (2024) https://doi.org/10.1117/12.3036522
Event: Third International Conference on Machine Vision, Automatic Identification and Detection, 2024, Kunming, China

Abstract

This paper intercepts the Web comment data in August 2015, and first analyzes the topics of these comment data through the LDA model, from high to low, which are 'Technology', 'Internet', 'Entertainment', 'Daily life', 'Daily study', which shows that people pay great attention to the topic of science and technology, which is in line with the theme that science and technology are the primary productive forces in today's era. Secondly, the word frequency map and text sentiment analysis are used as supplementary analysis, first through the word frequency map, the high-frequency words in these data are analyzed, and the top three high-frequency words are 'share', 'diamond' and 'China', which benefits from the rapid development of the Internet, so that people can share on the Internet daily, follow dramas and discuss China's development. Then, secondly, the positive sentiment words and negative sentiment words of this data are analyzed through text sentiment analysis to obtain which words are related to positive sentiment content, including 'diamond', 'China', 'data' and so on, which words are related to negative sentiment content, including 'share', 'president', 'phone' and so In summary, when dividing topics through the LDA model, the text data can also be supplemented by drawing word frequency maps and text sentiment analysis.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

ZhengPu Yue "Classification of Sina Web popularity topics based on LDA model", Proc. SPIE 13230, Third International Conference on Machine Vision, Automatic Identification, and Detection (MVAID 2024), 132300O (16 August 2024); https://doi.org/10.1117/12.3036522

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Internet

Reflection

Diamond

Analytical research

Clouds

Data transmission

Show All Keywords

Keywords/Phrases

Search In:

Publication Years