Research On Expert Resources Based For The Handling Online Negative Word Of Mouth

The booming growth of the online negative word of mouth(ONWOM)makes a big influence and brings huge loss to the enterprise,and the traditional service personal based online negative word of mouth handling method can no longer efficiently solve these ONWOM in the social media platform.How to handle such lager number,scattered distribution and rapid spread ONWOM has become a big challenge for enterprise.This thesis analyzed the demand and experts resource of ONWOM for complaint handling,defined the expert resources based on ONWOM handling,analyzed the influence factor of experts and three dimensions — — information,emotion and social capital,and designed the indicators of expert finding based on these dimensions.This thesis took the knowledgeable users in the social media platform into consideration,which are experts who have ability to handle with the ONWOM.Taking advantage of them will give a hand to enterprise to solve the ONWOM.Based on this idea,this thesis constructed an expert based online negative word of mouth handling mode,analyzed the related subject,including enterprise,complaints and experts,designed the system structure and working mechanism,and proved that involving expert in handing ONWOM does decrease the number of ONWOM by simulation experiment,and proved the feasibility of expert based mode.The key to solve the problem is finding out these experts from the social media platform,so this thesis proposed the expert finding method based on ONWOM handling,crawl the web data,use text analysis,sentiment dictionary and so on to calculate these indicators,trained the expert finding model by information,emotion and social capital dimension.The results proved that sentiment factor is useful in find expert and the three dimension model has the optimal performance in finding expert.The research result of this thesis provided a method for the enterprises,users and social media platform.