Research On Quality Of Answers In Q&A Community With Sentiment Analysis

Q&A Community is a social and socialized and platform where knowledge and experience can be exchanged.The sociality relies on the conversations about questions and experience.Much research has been done on this part,mainly using the social network analysis and link analysis to rebuild the network of the community.Improvements have been made on the operational mechanism,communication mechanism and user relationship.In addition to the social research,community is born as a result of socialization.The contents,no matter the topic and question,or the answer and comment,are all socialized.All the topics are created and maintained by users.All the questions are corrected and answered by users.All the answers are endorsed and commented by users and even all the comments are endorsed and replied as a circle.The socialization is both promoting and blocking it.This essay researches on the sociality of the Q&A community.It starts with the judgment of the answers in the community and moves on to its inner part to find an indexer to quantitate the judgments.The essay doesn't focus on the nature of answers but carries on to the comments to the answers.It concludes two features——the degree of professionalism and the value of sentiment analysis.It makes the sums of the weighed comment values and the professionalism of the author as predictors of the quantitate quality of answers.Firstly,the essay create a framework for crawling data and store the crawled data in Excel format.Then it describes the general feature distribution using statistical methods and finds that different types of topic vary in the feature of the total number of answers,answer votes,comments and comment votes.There are more votes on answers than comments.After that,it preprocesses the crawled data considering by natural language process and summarize the processed data into predict variables and observe variables.In the scatter plot,we can see the sparsity of data features as to make the data abnormal.By correlation analysis,some closely related factors are picked out as the candidate members of the final model.Finally it models the data with regression and comes to the conclusion that the quality of answers can be measured by the professionalism of authors,numbers of the comments and part of the positive sentiment scores comprehensively.In detail,positive sentiments of comments have more power over the quality of answers,although negative sentiments differ in the extent of effect according to the inner property of topics.Apart from the sentiment factors,the total number of answers and the authority of answerer also play essential parts and provide more complementary information.