Analysis methods of opinion leaders in online forums

Abstract

The invention provides a method for analyzing an opinion leader in a network forum. The method comprises the following steps of: computing the influence between any two post persons by comparing to generate a conversation link-based stepped computing time with a stepped evaluation method; computing the influence of any post person in a conversation link in the entire conversation link; computing an evaluation index of a plurality of conversation links in a topic and the overall influence of a post person I; counting attribute characters, i.e., the popularity rating of a post, the number of posts, the quantity of relies and online histories based on participants; portraying statistical data of basis behaviors of netizens in a forum; and comprehensively computing an opinion leader value. The analysis of a network opinion leader is performed in a specific block of the network forum and is limited in a certain topic or field, evaluation is performed on the aspects of the counted attribute characters of the netizens and the posting language materials of the netizens in the topic or field, the score of each netizen is computed according to a reasonable weight, and a person with the highest score is the opinion leader in the topic or field.

Description

technical field [0001] The invention relates to a method for analyzing public opinion leaders in network forums, and belongs to the technical field of network forum analysis methods. Background technique [0002] In 2002, Japanese scholar Matsumura et al. proposed an "Influence Diffusion Model" (IDM) based on online community communication, aiming to distinguish the types of network roles from the two aspects of text content and communication network, and to distinguish What kind of participants are in the network, the characteristics of the participants, and the roles they play in network communication, etc., to screen out the opinion leaders. The IDM model has obvious advantages. It enables the quantification of the corpus influence of the poster in the network, and facilitates the identification of network opinion leaders based on corpus. But the simple influence diffusion model obviously has two major flaws. One is that when the corpus-based dialogue chain has simple c...

AI Technical Summary

Problems solved by technology

However, the simple influence diffusion model obviously has two major flaws

One is that when the corpus-based dialogue chain has simple corpus during the transfer process or the post has no word intersection with the previous post, the influence of the dialogue chain will inevitably decrease sharply or be completely "broken".

According to the IDM model algorithm to calculate the influence based on the corpus, it will be difficult to get the correct result, because the "breakage" of the dialogue chain makes the influence of the superior post on the subordinate post become zero

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