e手包辦新聞網

本研究收集2019年至2020年間刊載於聯合報的所有新聞標題，經由斷詞、詞性、情緒分析及NRC Emotion Lexicon等技術，輔以網站開發，提供讀者能夠篩選各類新聞情緒之平臺—「e手包辦新聞網」，囊括11種情緒分析：正面、中性、負面、憤怒、預期、厭惡、恐懼、喜悅、悲傷、驚喜與信任，期望能夠以客觀方式呈現與提醒讀者每篇新聞的情緒。為讓閱讀體驗更具個人化特色，進一步規劃了會員制度、推播通知、推薦讀者感興趣的新聞情緒類別內容，以及運用文字雲、折線圖及長條圖等視覺化圖表，顯現標題情緒分析之結果，以利讀者掌握當今時下熱門事件，或對於新聞事件之情緒演變等資訊一目了然。

關鍵字

新聞標題；情緒分析；情感分析；標題分類；新聞網站

並列摘要

This research collects all newspaper titles published in the United Daily News from 2019 to 2020. Through word segmentation, part-of-speech tagging, sentiment analysis, NRC Emotion Lexicon and other technologies, supplemented by website development, it provides a platform for readers to filter various news sentiments: ＂E-hand News,＂ including 11 kinds of emotion analysis: positiveness, neutrality, negativeness, anger, anticipation, disgust, fear, joy, sadness, surprise and trust. It is expected to present and remind readers of the emotions of each news article in an objective manner. In order to make the reading experience more personal, we have further planned the membership system, push notifications, recommended news sentiment categories that readers are interested in. In addition, we have adopted visual charts such as word clouds, line graphs and bar graphs to show sentiment analysis of newspaper titles. As a result, readers can easily grasp current popular events or the emotional evolution of news events at a glance.

並列關鍵字

News titles ； Sentiment analysis ； Emotion analysis ； Title classification ； News website

參考文獻

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McIntyre, K. E., & Gibson, R. (2016). Positive news makes readers feel good: A “Silver-Lining” approach to negative news can attract audiences. Southern Communication Journal, 81(5), 304-315. doi:10.1080/1041794X.2016.1171892

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