Text Mining Of Attitudes Toward Depression On Chinese Social Media

Depression is a common mental disorder,which can lead to the decline of people’s ability to experience happiness and the impairment of physical function,and has the characteristics of high recurrence rate,high prevalence rate,high self mutilation rate and high suicide rate.With the normalization of COVID-19,the prevalence of depression and anxiety has been greatly affected by the spread of the epidemic.Although relevant studies have pointed out that if patients with depression can see a doctor in the early stage,it will improve the curative effect.However,patients with depression are deeply affected by the sense of shame,and will avoid medical treatment in the rejection of the outside world and themselves.Improving people’s attitude towards depression on social media will help to create a good social opinion environment for patients with depression in real life.The purpose of this study is to improve the public’s attitude towards depression on social media in China,so we need to first understand the focus of discussions on depression from different groups on social media,quantify the possible misunderstandings of the public by comparing the concerns and attitude tendencies of different groups,and give more targeted suggestions for the areas where knowledge related to depression needs to be popularized.Firstly,based on the machine learning model,this paper divides the groups discussing depression into three categories: patients with depression,people around patients with depression and others,then establishes the LDA topic model to mine and compare the concerns of different groups on depression.Finally,classifies the documents into corresponding topics based on the principle of maximum probability,and identifies the emotional tendencies of the documents under the same topic based on the emotional dictionary.Through Comparing the composition of different emotional attitudes of different groups under the same theme,this paper explores the public’s attitude towards depression on social media and gives more targeted suggestions on the areas where knowledge related to depression needs to be popularized.Through the analysis,it is found that people around patients with depression hold a more friendly attitude towards patients with depression than other groups,and it still needs some efforts to build a more acceptable online public opinion environment for patients with depression.In terms of etiology,compared with the people around patients and patients with depression,others lack a certain understanding of the negative campus experience of patients with depression.The most concerned topic of the public is the original and nuclear family of patients with depression.In terms of symptoms of depression,the public focuses on physical symptoms and attitude towards life（extreme behaviors）,and some ignore the emotional,mental and cognitive problems brought by depression to patients.In terms of the impacts of the disease,a considerable number of patients have positive attitudes toward the impacts brought by depression.According to the analysis results,this paper gives the following suggestions: it is suggested that the relevant departments should strengthen the popularization of the knowledge related to depression,and the relevant departments should focus on the influence of campus experience on depression,the emotional distress,mental distress,brain cognitive changes of patients with depression,and the spiritual strength that patients with depression can still explore the positive meaning in the face of disease.