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| Title: | 新聞輿情與民意偵測追蹤之研究－大資料之研究取向
A Study of News Sentiment & Public Opinion Detection and Tracking－A Big Data Research Approach |
| Authors: | 鄒函升 |
| Contributors: | 楊建民
鄒函升 |
| Keywords: | 文字探勘
意見探勘
事件偵測追蹤
民意
大資料
Text Mining
Opinion Mining
Events Detection and Tracking
Public Opinion
Big Data |
| Date: | 2013 |
| Issue Date: | 2014-07-29 16:04:09 (UTC+8) |
| Abstract: | 隨著人們習慣的改變，從網路上獲取新知漸漸取代傳統媒體，網路新聞比起傳統新聞有著即時且大量的特性，然而面對快速又大量的新聞訊息，人們更加難以去整理吸收。此外，新聞是經過媒體驗證和包裝過的社會輿論，其客觀地闡述事件的發生與經過，亦可以藉由新聞投射出民情民意。因此，要如何在大量的資料中有效且正確地找到想要的資訊是很重要的議題，但更重要的是如何在這些大資料(Big Data)中，發現、解決問題、甚至預測未來。本研究在龐大的資訊海中，除了運用新聞偵測追蹤技術幫助使用者更有效的尋找到資訊之外，更將在這大量新聞中利用意見探勘技術分析新聞事件之輿情，了解社會情緒氣候樂觀或悲觀。
在研究過程撰寫爬蟲程式自動蒐集中央新聞社2013年6月10日至2014年5月6日共14,729篇的政治類新聞，運用Single-pass Clustering加時間概念進行新聞偵測、kNN分類法進行新聞追蹤，將結果群集再次利用k-means做第二次分群，以提高事件品質，最後利用意見探勘技術進行輿情分析。
在研究結果中，我們將結果的新聞事件群集結果與民間的民意調查資料互相比較。其中負面的新聞事件對照TVBS民意調查中心的資料，可以發現在事件輿情與熱門區間皆有一定相關性。此外，也發現負面的新聞事件大約都持續四週左右，可以在事件爆發時，做好相關的規劃措施，避免社會情緒持續低落。在整體新聞輿情方面，利用整體新聞輿情趨勢，對照台灣指標民調公司發布的行政院長不滿意趨勢，發現有高於七成的相關性。從研究結果可看出能有效的反映出社會民情。
本研究在資料科學(Data Science)的現今中，提出一種即時且省資源的觀察新聞事件輿情與社會氣候方式。在未來希望加入不同新聞媒體或更多元的意見來源(社群網站、部落格)，來更真實直接反映出社會輿情，或可成為一種新的洞察民情之方式。
Recently, acquiring knowledge and current events from the Internet is gradually replacing traditional media. However, It is more difficult for people to organize and absorb because of the huge amount of news information. In addition, the news is the social conditions that verified and packaged through the media. It implies the public sentiment and public opinions. Therefore, how to effectively and accurately find the information in a large amount of data is a important issue. More importantly, founding & solving problem and even predicting the future is significant issue in this current. In this study, in addition to the use of detection and tracking technique to find the information more effectively, we also apply opinion mining to analyze news sentiment to understand about the optimistic or pessimistic social conditions.
In this study, we write a program to collect the political news automatically from The Central News Agency. And then applying event detection and tracking algorithm for classification and opinion mining for sentiment analysis.
In the conclusions, we take public opinion polls to valid our results, founding between the news sentiment and public opinion polls exist a certain relevance. Besides, it found that all the negative news lasts about four weeks at peak periods. Overall news sentiment trends have the exceeding seventy percent correlation with the dissatisfaction index of Premier. The results can be effectively reflected the public opinion.
In the data science of current, we propose a real-time and resource saving way to observe the news events and society. In the future, we will plan to add various media sources to reflect directly the real public opinion and even become a new way to insight into the public opinion. |
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| Description: | 碩士
國立政治大學
資訊管理研究所
101356032
102 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0101356032 |
| Data Type: | thesis |
| Appears in Collections: | [資訊管理學系] 學位論文
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