Quantifying The Intensity Of Emotional Expressions Used In Network Media

In recent years,network media has greatly enriched people's life.Due to its brief writing,convenient publishing and real-time interacting,get news,upload and share photo or video etc.,becomes very popular.More and more people are actively sharing information with others and expressing their opinions and feelings on network media.Analyzing emotion hidden in the information can benefit network media marketing,branding,customer relationship management and monitoring public opinions.Currently,most of the emotional analysis is on English network media,while Chinese network media emotional analysis is still at the initial stage.Emotional analysis is to identify the emotional tendencies of the network media messages,that is to classify users' emotions into positive,negative and neutral.By learning from the traditional text emotional analysis,we analyze the emotional tendencies of network media based on the characteristics of Chinese microblog.Firstly,summarize and organize the existing resources.Then,use the extended Semantic Orientation Pointwise Mutual Information to perform experiments on the Chinese Weibo microblog and build an emotional dictionary for Chinese Weibo microblog.Based on the diversity of expression forms of Weibo microblog,we conduct some preprocessing on the microblog text.We use the emotional words in the microblog text as feature selection method,and process the negative words,adverbs of degree,exclamatory sentence,rhetorical question,and emotional signs in the microblog accordingly.And finally obtain the emotional tendenciesby computing the weighted sum of various aspects of microblog messages.A system of emotional tendencies analysis for Weibo microblog is implemented in this paper.Basis of a comprehensive study of this paper related scholars at home and abroad to network media in the media Weibo micro blogging network information for the application background,users view information about the tweets included.This study attempts to use natural language processing technology to address the emotional words to quantify the intensity and emotion word modified matching between components and modified.In this article,based on objective includes four aspects,first of all for the statistical characteristics and domain rules in the field of words,extracted one area of the field of words.Namely tweets.Secondly,with the introduction of a news aggregate,calculate any similarity between the two news words.By clustering to identify group's most representative benchmark appraise word;you can get any of the words in the sentiment and strength on the basis ofthese benchmarks words.Third,it is by building emotional dictionary with Vote-AdaBoost(Adaptive Boost)method for object and subject recognize to get the sentiment of the text.In calculating the text sentiment,also considered the impact of negative words and extent of the sentence adverb.Fourth,the use of natural language processing techniques Natural Language Processing Natural Language Processing The original of this pretreatment,using syntactic analysis,carried out in-depth analysis of the sentence by the words dependencies,get dependency relationship modified key ingredient,calculated Emotional Words modified theme,and the theme of the sentence discussed emotional analysis.