Fine-grained emotion analysis improvement method based on emotion word embedding

A technology of sentiment analysis and sentiment words, which is applied in the field of sentiment analysis of Chinese texts, can solve problems such as not considering sentiment information, and achieve good sentiment classification results

Active Publication Date: 2019-06-25
SHANGHAI MIDU INFORMATION TECH CO LTD
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Problems solved by technology

However, these methods have certain limitations in sentiment analysis tasks: word embedding implements many NLP tasks by learning low-dimensional continuous value vector representations of word...

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  • Fine-grained emotion analysis improvement method based on emotion word embedding
  • Fine-grained emotion analysis improvement method based on emotion word embedding
  • Fine-grained emotion analysis improvement method based on emotion word embedding

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Embodiment 1

[0106] In this embodiment, the method for sentiment analysis based on embedding of sentiment words proposed in this patent is applied to the comment data of the online shopping platform.

[0107] Step 1: Acquisition, manual labeling and preprocessing of text datasets. Specifically, the following steps are taken:

[0108] A. Collect online comment data for sentiment analysis tasks;

[0109] B. Artificially label the sentences in all online comment data. This patent divides the emotional labels into three types of emotional labels: "positive, negative, and neutral". After labeling, each sentence corresponds to an emotional label;

[0110] C. Perform preprocessing on the text data set, including text segmentation, deletion of special symbols and stop words, where text segmentation refers to dividing sentences in the text data set into individual words. The word segmentation tool used is the Chinese Academy of Sciences word segmentation tool ICTCLA2018. Since the network text d...

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Abstract

The invention discloses a fine-grained emotion analysis improvement method based on emotion word embedding. The method comprises: obtaining of a text data set, manual labeling and preprocessing; calculating a semantic word vector corresponding to each word in the text data set; obtaining a set of sentiment words; calculating a group of emotion phrases corresponding to each word in the training data set; and calculating an emotion word vector corresponding to each word in the training data set; constructing emotion word embedding corresponding to each word in the training data set; and trainingthe classifier to obtain a fine-grained emotion analysis model. According to the method, priori sentiment knowledge is combined with a word embedding model, and sentiment word embedding suitable forfine-grained sentiment analysis is constructed for sentiment analysis. The emotion information of the word level can be better identified, the emotion of the user can be described more accurately in afine-grained mode, and the method can be used for fine-grained emotion analysis tasks such as consumption habit analysis of the user and comment analysis of the user on commodities.

Description

technical field [0001] The invention belongs to the technical field of Chinese text sentiment analysis, and in particular relates to an improved fine-grained sentiment analysis method based on sentiment word embedding for Chinese short texts such as microblogs and network comments. Background technique [0002] With the rapid development of the Internet, millions of people use social networks every day, such as Weibo, Tieba and other online platforms to express their views on products, services, news, events, etc. Analyzing the opinions or opinions expressed by users is very important for marketing professionals and researchers. Sentiment analysis of Weibo texts has become increasingly important due to the popularity of Weibo in Chinese society. Since 2013, the China Computer Federation (CCF for short) has specially set up the Chinese Weibo sentiment classification evaluation task in the second Natural Language Processing and Chinese Computing Conference (NLPCC for short), ...

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Application Information

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IPC IPC(8): G06F16/35G06F17/27
Inventor 畅帅李芳芳毛星亮施荣华石金晶胡超
Owner SHANGHAI MIDU INFORMATION TECH CO LTD
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