Search for Depress Tendency: An Analysis on Chinese Micro-Blog Texts

• Main Authors: Ren, Zhe Li, 任喆鸝
• Other Authors: Chen, Pai Ling
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/6vy83g

碩士 === 國立政治大學 === 新聞研究所 === 103 === This research aims to answer the following questions:(1)What are the characteristics of micro-blog writing by the depressed tendency people? (2)How to identify the text in social media? Ten Wei-bo users with identified depressed tendency were chosen as starting points of snow-ball searching, and 127 users were located. A total of 20748 messages from this group of the users was collected as the dataset. Multiple methods were applied to analyze the texts: content analysis, qualitative text analysis, word frequency analysis and word co-occurrence. The result indicated that: (1)Through the coding of the text tone, mood, theme and degree of depression, we find out that in micro blog writing, the depressive tendency uses 62% of the negative tone and 25.1% of the blue text. Among them, higher negative and degree of depression of writing subjects are "self", "family", "suicide" and "sleep disorder". (2)Through deep qualitative analysis of "self" and "affection" depressed writing, the "self loathing" and "don't understand" in their mind are the most unforgettable. (3)Because the depressed people have the features of "suicide" and "sleep disorder", through the analysis, we find that through theme related words, it is helpful in the identification of the depression text. Among them, the "sleep disorders" co-occurrence words depressed text identification is up to 74%, and "suicide" co-occurrence words depressed text identification degree is 34 %.In the future, through the computer, we can further optimize the method, and enhance the degree of identification of depression text.