本文選題：數(shù)據(jù)挖掘 + 群體事件��； 參考：《上海交通大學(xué)》2014年碩士論文

【摘要】：隨著我國經(jīng)濟(jì)快速發(fā)展和社會(huì)的轉(zhuǎn)型，近幾年頻繁出現(xiàn)的各類群體事件給人們的正常生產(chǎn)和生活帶來了極大的困擾。而目前決策者們的處理效果卻不甚理想，如何處理好群體事件和群體事件演化、發(fā)展的內(nèi)在機(jī)理成為了眾多學(xué)者研究的熱點(diǎn)。 與此同時(shí)，互聯(lián)網(wǎng)的快速普及為人們提供了表達(dá)訴求的平臺(tái)，網(wǎng)絡(luò)輿情管理成為當(dāng)下眾多學(xué)者研究的熱點(diǎn)。網(wǎng)絡(luò)輿情的屬性決定了網(wǎng)絡(luò)輿情是把雙刃劍，一方面能夠幫助弱勢群體解決訴求，另一方面也可能因?yàn)槔貌划?dāng)而造成更大的損失，研究網(wǎng)絡(luò)輿情管理的重要性日益突出。由此，本文主要針對群體事件網(wǎng)絡(luò)關(guān)注度與群體事件本身特征之間的關(guān)系展開研究和討論，旨在為群體事件輿情預(yù)警和預(yù)判提供可行性建議。 本文基于以上出發(fā)點(diǎn)，通過對群體事件典型案例的分析，，建立群體事件案例庫表示框架，搜集自2010年以來的各類群體事件加入案例庫，為群體事件案例分析和案例推理提供基礎(chǔ)數(shù)據(jù)支持。其次，在學(xué)習(xí)和理解群體事件領(lǐng)域知識(shí)的基礎(chǔ)上，本文建立了基于繼承關(guān)系的群體事件本體，為后續(xù)數(shù)據(jù)挖掘提供了基礎(chǔ)數(shù)據(jù)結(jié)構(gòu)。再次，本文在傳統(tǒng)ID3算法的基礎(chǔ)上，融合繼承關(guān)系本體，設(shè)計(jì)了基于本體的ID3改進(jìn)算法，為群體事件網(wǎng)絡(luò)關(guān)注度影響因素研究提供了工具；最后，運(yùn)用基于本體的ID3改進(jìn)算法，對群體事件網(wǎng)絡(luò)關(guān)注度的影響因素進(jìn)行了訓(xùn)練，得到了群體事件網(wǎng)絡(luò)關(guān)注度的分類規(guī)則，通過規(guī)則的分析，了解群體事件網(wǎng)絡(luò)關(guān)注度與群體事件本身特征之間的內(nèi)在邏輯和聯(lián)系，為群體事件輿情預(yù)警提供了可行性建議。
[Abstract]:With the rapid economic development and social transformation in China, the frequent occurrence of various group events in recent years has brought great problems to people's normal production and life. At present, the effect of the decision makers is not very good. How to deal with group events and the evolution of group events, the internal mechanism of development has become a hot spot of many scholars. At the same time, the rapid popularity of the Internet provides a platform for people to express their demands. The attribute of network public opinion determines that network public opinion is a double-edged sword. On the one hand, it can help the vulnerable groups to solve their demands, on the other hand, it may cause more losses because of improper use. The importance of studying the management of network public opinion is increasingly prominent. Therefore, this paper mainly focuses on the research and discussion of the relationship between the network attention of group events and the characteristics of group events, in order to provide feasible suggestions for public opinion early warning and prediction of group events. Based on the above starting point, through the analysis of the typical cases of group events, this paper establishes the case database representation framework of group events, and collects all kinds of group events since 2010 to join the case database. To provide basic data support for group event case analysis and case-based reasoning. Secondly, on the basis of learning and understanding the knowledge of group event domain, this paper establishes a group event ontology based on inheritance relation, which provides the basic data structure for subsequent data mining. Thirdly, based on the traditional ID3 algorithm, this paper designs an improved ID3 algorithm based on ontology, which provides a tool for the study of the influencing factors of network concern of group events. Finally, the improved ID3 algorithm based on ontology is used. The influencing factors of group event network attention are trained, and the classification rules of group event network attention degree are obtained. Through the analysis of the rules, Understanding the internal logic and relationship between the network attention and the characteristics of group events provides feasible suggestions for public opinion warning of group events.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP311.13;D631.43

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本文編號(hào)：1884620