臺灣博碩士論文加值系統

隨著資訊科技的進步，網際網路的使用日趨普遍，投資人可以隨時隨地取得欲投資目標的各種資訊，新聞媒體的訊息會帶給投資人悲觀或樂觀的預期心理進而影響股市的成交量，所以新聞媒體的訊息往往是投資人參考的指標之一。而我們要探討是一個新聞媒體訊息的情緒態度以及新聞訊息散佈的數量在社會網路中的擴散過程，進而去觀察社會大眾對於股票購買持股的影響。
先前有許多學者提出眾多用來探討意見交換過程的輿論動態模型，但只著重在意見交換，社會大眾不會互相討論並且互相影響，也提出了很多用來探討創新擴散的門檻模型及其應用，但個體意見態度和意見擴散門檻並不會互相影響。本研究整合輿論動態模型和決策門檻模型，透過電腦模擬實驗，在規則、隨機、小世界、無尺度四種理論網絡上，探討意見交流的輿論動態，而且能夠觀察出持有購買股票的動態。
我們提出的模擬中，投資人之間可以互相溝通，並且會隨時間不同而持不同的態度。也能夠依照投資人的決策門檻值及投資友人對於新聞訊息的實質行為（或持股、購買等）結果來採取後續的決策。經由模擬實驗，我們發現修改過後的模擬模型更能真實的反應出社會大眾接受一個爭議股票新聞訊息時的各種可能現象，我們整理出在各種社會狀況時新聞訊息的傳播擴散過程，希望能作為往後投資策略或是傳播動態研究的一個參考，並在此基礎上探索更細部的因素。

With the advancement of information technology and the internet has become an inevitable trend, investors can obtain various information from their investment targets anytime and anywhere. Messages from the news media will bring investors pessimistic or optimistic expectations and affect the trading volume of the stock market. Therefore, messages from the news media are often one of the indicators that investors refer to. And what we want to explore is the content of a news media message and the diffusion process of the number of news messages spread in the social network, then observe the impact of the public on the trading volume of stocks.
Many scholars have proposed many dynamic models of public opinion to discuss the process of opinions exchange previously; however, they only focus on the exchange of opinions, and the public will not discuss and influence each other, although they have also proposed many threshold models to investigate the diffusion of innovation, it will not inter-relation between the attitudes of different agents and the individual thresholds. This research integrates the public opinion dynamic model and the decision threshold model, to discuss the public opinion of opinion exchange on the four theoretical networks of rule, random, small world, and scale-free through computer simulation experiments, and observe the dynamics of people who are ready for buying stocks.
In our simulation, investors can communicate with each other and have different attitudes over time. It can also take follow-up decisions based on the investor's decision-making threshold and the results of the actual behavior (holding, buying, etc.) of the investor's news information. Through simulation experiments, we found that it can more truly reflect the various possible phenomena when the public accepts a news message with controversial stock by adopting the modified simulation model. We have sorted out the dissemination and diffusion process of news information under various social conditions, we hope that it can be used as a reference for future investment strategies or dissemination dynamic research, and more detailed factors can be explored on this basis.

中文摘要 IV
英文摘要 V
圖目錄 X
表目錄 XIV
第一章 緒論 1
第一節 研究動機與背景 1
第二節 研究目的 4
第三節 研究流程 5
第二章 文獻探討 7
第一節 新聞情緒 7
第二節 文字探勘 8
第三節 社會網路(Social network) 10
第四節 訊息動態模型（Opinion dynamics model） 12
第五節 決策門檻模型（Decision threshold model） 14
第六節 創新擴散 15
第三章 資料來源與研究方法 17
第一節 資源來源 17
第二節 文字資料處理 18
第三節 模型設計 19
第四章 實證結果 31
第一節 敏感度分析 31
第二節 規則網路（CellularnAutomata, CA） 32
第三節 隨機網絡（Random Network, RN） 41
第四節 小世界網絡（Small World Network, SWN） 51
第五節 無尺度網絡（Scale-Free Network, SFN） 61
第六節 不同網絡拓譜特性對實驗結果影響整理、比較 71
第五章 結論 81
第一節 結論 81
第二節 未來研究建議 82
參考文獻 84

一、中文部分
1. 林宜萱 民101，財經領域情緒辭典之建置與其有效性之驗證-以財經新
聞為元件，國立台灣大學會計學研究所碩士論文
2. 蔡文翊 民96，小世界社會網絡演化模型:階段性需求於社交網絡拓樸動態的影響，國立交通大學資訊科學與工程研究所碩士論文
3. 徐鈺瀅 民97，改良有界信心模型探討大眾媒體與小眾媒體對於意見動態的影響，國立交通大學資訊科學與工程研究所碩士論文
4. 高嘉宏 民 99，輿論溝通對爭議性技術/觀念之擴散動態與過程的影響及交互作用，國立交通大學多媒體工程研究所碩士論文
5. 謝昀容 民 108，整合輿論動態模型和創新擴散模型探討叫好不叫座現象，私立長庚大學資訊工程學系碩士論文
6. 吳昱萱 民106，股價波動與財務預警-數據分析觀點，國立政治大學會計學系碩士論文
7. 胡育誠 民108，應用新聞情緒指標結合隨機森林演算法預測股價漲跌趨勢，國立高雄科技大學金融資訊系碩士論文

 
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