Economic and financial behavior analysis system model based on social media

Abstract

The invention discloses an economic and financial behavior analysis system model based on social media. The economic and financial behavior analysis system model based on the social media is characterized in that the system comprises a crawler, a database / indexer and an analyzer, wherein the crawler is mainly in charge of data collection; the database is divided into two parts which are structural data and unstructured data, when indexes are built, each user and each piece of microblog are respectively configured with a global ID according to collected data information, and information in different databases is aligned and searched; the analyzer is the core of the system and comprises a topic analysis submodule, an entity identification submodule, an action recognition submodule, a message tracking submodule, an emotion analysis submodule and a community cluster analysis submodule. The economic and financial behavior analysis system model based on the social media can effectively and accurately collect user information, conducts relatively complete archiving and arrangement on user data, builds a user information base, and provides the users with push of messages which are concerns of the users according to the user information base.

Description

technical field [0001] The invention relates to a social media-based economic and financial behavior analysis system model, which belongs to the field of computer software applications. Background technique [0002] With the development of Web2.0, more and more people hope to express their views freely on the Internet. These opinions can be publishing or reposting a piece of news or news, or commenting on a certain piece of news, or it can be a venting of one's own emotions. Traditional discussion boards, BBS, and blogs are gradually unable to meet the impact of high-speed information. In this context, Weibo, as a new type of social media, is attracting more and more attention from users on the Internet, forming a great stickiness and coverage. As a result, these massive and time-sensitive data bring great opportunities and challenges. [0003] First, there are big opportunities in big data. Paul Hawtin of Derwent Capital Markets on Wall Street uses computer programs to ...

AI Technical Summary

Problems solved by technology

[0004] Second, massive data and due to the limited word count and timeliness of Weibo publications pose great challenges to data analysis and processing

Therefore, how to extract useful information and knowledge from short texts, and even users' emotions and opinions is more difficult

At the same time, more time-sensitive, we cannot save all information