大多數的人們會將他們的正面情緒和負面情緒寫進部落格中，本論文的重點在透過分析部落格文章中的負面情緒來預測部落客的憂鬱傾向。本研究提出多重消極因素分析模型(Multiple Passive Factors Analysis Model)和情緒趨勢分析(Emotion Trend Analysis)方法用以判斷部落格作者是否具有憂鬱情緒。我們從痞客邦(PIXNET)收集了大量的部落格文章，用以觀察、訓練與實驗，並且利用中央研究院CKIP斷詞系統做文章斷詞處理。同時我們使用從實際罹患憂鬱症患者和自殺者案例的部落格文章中透過半自動萃取技術抽取負面情緒、觸發事件、症狀和負面想法詞彙做為辭典。四個辭典被運用在多重消極因素分析型的計算中，每一篇部落格文章皆會得到一個情緒分數(Emotion Score)。我們針對每一個部落格使用程式自動繪製情緒趨勢曲線(Emotion Trend Curve)，將其所有的情緒分數依照時間序列連成一條情緒分數曲線(Emotion Score Curve)。這種情緒趨勢中出現由低分到高分、持續維持在高分或是高頻率變動的情緒分數可以幫助預測部落格作者是否具有憂鬱傾向。實驗結果證明本研究提出的方法可以明顯判斷實際患有憂鬱症患者部落格和正常人部落格，而在判斷含有憂鬱情緒的部落格方面也具有86.92%的正確性。在未來這項研究期望和專業醫師或醫學專家合作，進一步驗證情緒分數和與其臨界值。另一方面也期望在不久的將來提供線上服務以幫助部落格使用者做憂鬱情緒的自我檢測。

Most of bloggers write affective articles with their positive or negative emotion in web blogs. This paper focused on analyzing negative emotions in web blogs to predict depression tendency of bloggers. The objective of this paper is to analyze blog posts for bloggers and use the proposed Multiple Passive Factors Analysis Model(MPFA) to predict the depression tendency of bloggers. We collect large amounts of blog posts in Chinese from PIXNET Taiwan. The posts were segmented using Chinese Word Segmentation System with Unknown Word Extraction and POS Tagging from ACADEMIA SINICA. Four categories of terms, including emotion, event, depression symptom related and negative thought, were semi-automatically extracted for each post. The emotion score is calculated for each post by the proposed MPFA model. We design a way of drawing emotion trend curve to present emotion trend of a blogger in a period of time. This emotion trend can help medical experts to predict the depression tendency of a blogger based on the three cases, including negative emotion scores changing from low to high and a duration keeping at high negative emotion score and frequent emotion variation. Experimental results showed that our proposed model is effective to predict bloggers’ depression tendency. The future work of this research is to provide predicted results to doctors or medical experts to verify reasonable negative emotion scores for depression patients and the threshold.

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