Study On The Influencing Factors Of Online Q&A Community's Answer Adoption In Emergency Context

In recent years,with the continuous development and progress of the Internet information technology and country's strong support for the Internet industry,the Internet has gradually penetrated into various fields,and the number of network users has also shown a year-on-year growth trend.The Internet has become a main channel for users to publish,spread and search information.Information expansion and time fragmentation have made users more inclined to spend less time and energy to obtain more accurate and higher-quality information.Under such background,the online Q & A community has gradually developed into one of the main channels for users to obtain online information and knowledge resources.Along with the dramatic increase of user amount and user-generated content,the quality of answers in the community is mixed,which has a certain impact on answer adoption and community reputation.How to improve answer adoption in community is particularly important for the community development,especially in the context of emergencies,exploring the characteristics of the answers and the factors that affect answer adoption does make a big difference to the long-term operation of the community and help users identify useful information.This paper studies the influencing factors of the online Q & A community's answer adoption in emergencies,which has theoretical value and practical significance.First,based on the Information Adoption Model(IAM),the hypothesis and influencing factor model of this research are constructed from two dimensions—the characteristics of respondent reliability and answer quality.It is believed that the characteristics of respondent reliability include the number of platform certifications obtained by the respondent,respondent's followers,etc.The characteristics of answer quality include text features such as text length,average sentence length,and non-text features such as the number of comments,the number of pictures and external links.Then,collect the data about answers and users under the "Pneumonia" topic essence section of Zhihu,com.Finally,the data is cleaned and analyzed.During data cleaning and processing,the sentiment dictionary-based sentiment analysis method is used to calculate the sentiment value of the answer content,and the average information entropy is incorporated into the Text Rank algorithm to extract topic keywords.During data analysis,the number of likes to answer is used to express the degree of answer adoption,then construct a Tobit regression model with the number of likes as a limited dependent variable,and validate the research model with valid samples obtained from the topic "Pneumonia",so the research is able to identify the factors affecting answer adoption in Zhihu.com under the emergency situation represented by "New Coronary Pneumonia".The research results show that: In an emergency situation,among the characteristics of the respondent reliability,the number of platform certifications,professional recognition and historical answering ability positively affect the answer adoption,while the number of followers has negative impact.Among the text characteristics of answer,the square of the answer length has a negative impact on the answer adoption,which illustrates the length of answer text and the answer adoption have an inverse U-shaped relationship.The average sentence length,emotional tendency,and number of topic keywords all positively affect the answer adoption.Among non-text features,the number of comments and pictures have a significant positive impact on the answer adoption,while the number of external links has a negative direction.The question answer interval has no significant effect in such context.