Public Opinion Analysis of Ruhun’s Listing: How Do Online Public Opinion Professionals Analyze Internet Public Opinion Cases?

Online information is diverse, segmented and complex. Searching and organizing such a vast volume of information and conducting internet public opinion analysis is no easy task. So how can we efficiently crawl and analyze this information?

From a practical perspective, with a relatively sound public opinion analysis system in place, mastering specific analytical methods is critical to improving the efficiency of public opinion judgment. At present, there is no standardized operating method or standard for internet public opinion analysis. Among the routine methods adopted by various departments nationwide, the main ones include manual browsing, keyword search, multi-document summarization, template coefficient method, online experiment method and case comparison method.

I. Manual Browsing Method

The manual browsing method refers to understanding online public opinion by manually checking various websites and pages. As this type of inspection consumes huge human resources, especially when facing massive internet data, a large number of personnel must be deployed to complete the task, hence the name manual browsing method. This method features accurate information retrieval, comprehensive content reflection and high public opinion reliability, but also suffers from slow report integration, massive labor input and potential omissions. The first three are advantages, while the latter three reflect its deficiencies and drawbacks.

II. Keyword Search Method

The keyword search method involves selecting key phrases as keywords based on the linguistic features of target public opinion information, and collecting such information via internet search engines, either manually or through automated systems. This method is more efficient than manual browsing, enabling timely extraction and display of relevant target public opinion information from web pages. It enjoys the benefits of clear objectives, high search efficiency and wide coverage. However, search quality is closely tied to the performance and settings of the search engine used. In particular, machine-driven keyword-based collection often lacks the flexible judgment and adaptive integration of human processing, frequently causing valuable public opinion information to be overlooked.

III. Multi-Document Summarization Method

The multi-document summarization method captures the essence of public opinion content in judgment by extracting summaries from documents involving target public opinion information. Initially used in public opinion reports to demonstrate the authenticity of content, it has gradually evolved into an independent method for internet public opinion judgment.

The selection and summarization of online public opinion documents can be done manually or assisted by automated systems through dedicated applications. Currently, automatic document summarization functions are widely integrated into developed public opinion analysis software systems.

IV. Template Coefficient Method

The template coefficient method establishes mature templates for internet public opinion scenarios based on historical analysis and evolutionary patterns, and extracts relevant effect coefficients as a statistical approach to public opinion judgment. Significantly different from the previous three methods, it is a data-driven approach that judges public opinion through modeling. It can be implemented manually or translated into automated programs for artificial intelligence simulation, thereby enhancing analysis efficiency. The theoretical and practical models provided by this method are still emerging; research institutions and professional departments have included it in exploratory studies and achieved initial progress.

V. Online Experiment Method

The online experiment method analyzes the evolution of public opinion incidents by simulating them within a virtual network environment. Strictly speaking, it is a research-oriented approach, mostly used by educational and scientific institutions to study predefined public opinion topics. It can also serve as an important supplement to practical public opinion judgment for analyzing current online sentiment. Based on the participant group, online experiments are divided into open and closed types.

An open online experiment studies public opinion on a certain issue among all internet users, representing real naturally occurring public opinion, albeit led by research institutions. A closed online experiment takes place on a specific local area network, with participants limited to controlled users within the network; it does not reflect real online public opinion but simulates discourse in a controlled experimental environment.

VI. Case Comparison Method

The case comparison method classifies past internet public opinion cases, builds a database, extracts core features as comparison coefficients, and uses them to benchmark and evaluate current public opinion incidents.

This judgment method relies on experience, essentially using historical cases as an inertial frame of reference to assess ongoing public opinion. Its advantage lies in relatively reliable analytical logic and abundant empirical data for reference. Its disadvantage is that it fails to reflect changes in external public opinion environments and internet infrastructure, and cannot establish an adaptive judgment framework aligned with shifting external conditions.

Naturally, no public opinion incident repeats exactly. Yet in an era of social transformation and technological innovation, external conditions change rapidly and exert an increasingly significant impact on online public opinion.

Relying solely on manual work for public opinion analysis can be laborious and inefficient. Therefore, assisting manual analysis with professional public opinion monitoring software such as Duoweisite Public Opinion Data Analysis System can greatly improve work efficiency.

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