Text sentiment analysis method

A sentiment analysis and text technology, applied in the field of artificial intelligence, can solve problems such as high cost, affecting the accuracy of text sentiment analysis, ignoring key information influencing factors, etc.

Pending Publication Date: 2021-12-28
XIAN UNIV OF POSTS & TELECOMM
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The invention relates to improving emotional evaluation systems for documents based on extracted data from both matrices. By utilizing this system, it can accurately identify important aspects like personality traits or moods associated with each document's content. This results in better understanding about how people behave over time compared to other existing techniques such as categorization into groups or subjective assessments.

Problems solved by technology

This patented technology describes an issue with manually analyzing social media posts due to factors like emotion overtly expressed during them (text). Current solutions require expensive equipment such as deep learning models trained from large amounts of data collected through experiments conducted at different times), which makes it difficult if done correctly without sacrificing important aspects of human perceptions about what they're feeling right now.

Method used

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  • Text sentiment analysis method
  • Text sentiment analysis method
  • Text sentiment analysis method

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Embodiment Construction

[0033] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0034] Furthermore, the drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repeated descriptions will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically separate entities.

[0035] This example embodiment provides a t

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Abstract

The embodiment of the invention relates to a text sentiment analysis method. The method comprises the steps that: a global vector and a word conversion vector are adopted to vectorize and train a target text, a first text vector matrix and a second text vector matrix of the target text are obtained, and the target text is a text to be subjected to sentiment analysis; key feature information in the first text vector matrix and key feature information in the second text vector matrix are extracted through a double-path attention mechanism, and enhancement processing and feature fusion are carried out on the key feature information; and classification processing is performed on the first text vector matrix and the second text vector matrix after feature fusion by adopting an activation function to obtain an emotion analysis result of the target text. According to the embodiment of the invention, based on the extracted key feature information and feature fusion, sentiment classification processing is realized, and more ideal text sentiment analysis accuracy is achieved.

Description

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Claims

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Application Information

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Owner XIAN UNIV OF POSTS & TELECOMM
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