以大數據探究網路色情新聞和輿論分析

Using big data to explore online pornographic news and public opinion analysis

黎萱(Li Hsuan)

指導教授 ： 蔣旭政

國立臺灣師範大學/國際與社會科學學院/大眾傳播研究所/碩士(2020年)

https://doi.org/10.6345/NTNU202000495

摘要

媒體商業化後，暴力、腥羶色新聞充斥於版面中，傳統媒體逐漸流於「小報化」、「八卦化」，基於上述研究動機，本研究有下列二項研究目的：一、瞭解臺灣新聞平台的小報化程度和變化趨勢；二、探討閱聽人對於這類新聞的回應，故有此研究。

本研究結合大數據分析法、滯後序列分析法深入探討，以Python網路爬蟲獲取《蘋果新聞網》、《聯合新聞網》、《ETtoday新聞雲》五年新聞，研究上述媒體的色情趨勢變化、最常使用色情詞彙之平台等，最後剖析色情比例最高之Facebook粉絲專頁，以滯後序列分析法分析留言，瞭解受眾對色情新聞之看法。

本研究蒐集了逾百萬則新聞資料，更彙整出各平台的色情數量、分類，如性犯罪、性交、色情、顯示裸露人體、色情照片及影片等，同時也發現最常使用色情詞彙之平台為《ETtoday新聞雲》、高頻色情關鍵字為「性侵」。研究發現，提出論點或證據、或對色情新聞表達中立客觀態度之閱聽人僅佔7%，相較認同色情內容之71% 留言有極大反差。

本文認為，在媒體大環境仍以小報化為主流時，閱聽人需提升媒體識讀之能力以杜絕媒體中夾雜的腥羶色、八卦新聞，除了簡短、趣味的新聞，閱聽人應將閱讀深度報導看作吸收思想養分、幫助展開深度對話的管道。

關鍵字

大數據 ； 小報化 ； 感官主義 ； 色情新聞 ； 序列分析

並列摘要

Since the commercialization of the media, violent and sensational news content has often been flooded in the layout. Traditional media has gradually evolved into tabloidization and sensation to understand the degree of tickness in Taiwan’s online news platform, and also study whether the readers pay for the news of inciting emotions.

This paper combines big data analysis and lag-sequential analysis to explore. Python crawler is used to obtain the 5-year news information of Appledaily, United Daily News, ETtoday. The key words of “sensational” are captured by word frequency analysis. Finally, the message of fans page of news website with the highest proportion of sensational news is discussed by sequence analysis method to understand the acceptance.

Taiwan's media and content are not only influenced by ideology and values. Under the trend of commercialization, the media environment has less objective and rational news content, but more sensational and gossip. 5 years news and a total of millions of news on the news network platform have been captured, and it has been found that the development of sensational news in Taiwan has slowed down gradually. Understand what are the most commonly used fishy words by journalists, and make an analysis and comparison of the comments of readers and listeners. At the end of this study, this research want to explore how readers should view gossip news and take the first step of change.

並列關鍵字

big data ； tabloidization ； lag sequential analysis ； sensationalism ； sensational news

參考文獻

英文部分

Adams, W.C. (1978). Local public affairs content of TV news. Journalism Quarterly 55 (4), 690–695.

Allen, M., D'ALESSIO, D. A. V. E., & Brezgel, K. (1995). A meta‐analysis summarizing the effects of pornography II aggression after exposure. Human communication research, 22(2), 258-283.

Altheide, D.L. (1976). Creating reality: how TV news distorts events. Beverly Hills: Sage.

Carrington, P. J., Scott, J., & Wasserman, S. (Eds.). (2005). Models and methods in social network analysis (Vol. 28). Cambridge university press.