推特是當今最受歡迎的微網誌平台，提供了使用者透過各式各樣的方式分享資訊，除了透過推特網站之外，還可以經由手機簡訊以及手機上的應用程式來發表訊息。現在每天有超過一千四百萬個活躍使用者，產生超過三千四百萬則訊息，所以推特成為了非常好的資源用來探勘大眾意見。傳統在網路上的意見探勘專注於分析特定領域的意見，例如電影、書本或是產品；利用使用者發表對特定產品的文章當作資源，然後分析這些文章的意見。但是都僅侷限對單一物件的意見進行探勘，這些方法在即時訊息流中並無法針對不同物件間進行比較，甚至找到比較標的。
在我們的研究中，我們希望透過意見探勘找出一個物件與其他物件間的競爭關係。此研究內，我們提出了兩物件競爭關係以及相對意見的想法來做競爭的辨識。本論文建構了一個架構於推特上進行競爭辨識的系統。方法部分分成兩個階段，資料處理階段將推特資料處理成有用的資訊；而排名階段會根據提出的物件競爭圖對相對意見做分析，並且整合所有意見以用來辨識出競爭關係。
我們的研究結果顯示：相對意見有助於我們辨識出競爭關係，而且我們提出的整合意見方法也對此問題研究結果有幫助。

Twitter, one of the most popular microblogging services allow users (twitterer) to post messages (tweet) through the website interface, SMS, or a range of Apps for mobile devices. It has over 140 million active users, generating over 340 million messages per day. As a result of rapidly increasing numbers of tweets, Twitter becomes a valuable source for mining people’s opinion and sentiment. Tradition opinion mining from general contents (Blog articles, review articles) on the web focuses on specific domains such as movie, book or consumer product. They gather lots of articles regarding the particular product, and analysis the opinion in the articles. Different from mining the opinion from particular objects, we want to know whether object A can be found when mining opinions from object B, and conclude the competition between object A and object B.
In this paper, we introduce the competition relation between two objects, and propose the idea of the relative opinion to identify the competition. We construct a framework to identify the competition in Twitter. Our method consists of two stages: First, the data process stage processes the raw data from Twitter and constructs the opinion conversions. The ranking stage mines the relative opinion between objects. This stage also aggregates the opinions to identify the competition.
Our result shows that the relative opinion is a good indicator to identify the competition. The opinion aggregation algorithm we proposed can help us to improve the result of the identification.

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