發(fā)布時間：2018-01-26 16:18

  本文關(guān)鍵詞： 網(wǎng)絡(luò)事件 網(wǎng)絡(luò)輿情 擴散規(guī)律 擴散模型 遺傳算法　出處：《山東財經(jīng)大學》2014年碩士論文　論文類型：學位論文

【摘要】：隨著大數(shù)據(jù)、4G高速網(wǎng)絡(luò)時代到來，實時交互、成本低廉的網(wǎng)絡(luò)事件對社會生活、政策法規(guī)、人民心態(tài)影響逐漸加深。事件監(jiān)控、輿論引導等問題引起廣泛重視。本文針對網(wǎng)絡(luò)事件發(fā)生的早期特征對其進行實時監(jiān)測評價，對其未來發(fā)展進行預(yù)測，以期預(yù)警和引導輿論的良性發(fā)展。 本文跟蹤收集大量網(wǎng)絡(luò)事件并記錄早期特征和最終影響范圍，全程評估及評價內(nèi)容，歸納總結(jié)了網(wǎng)絡(luò)事件擴散的時間規(guī)律、熱度規(guī)律和生物時鐘規(guī)律、不同網(wǎng)絡(luò)事件信息篩選規(guī)律和同一網(wǎng)絡(luò)事件信息篩選規(guī)律。 本文通過實時網(wǎng)絡(luò)事件歸類、擴散性和傾向性檢測，建立網(wǎng)絡(luò)事件數(shù)據(jù)間的邏輯關(guān)系，，依據(jù)網(wǎng)絡(luò)事件擴散規(guī)律建立了網(wǎng)絡(luò)事件擴散模型。評價網(wǎng)絡(luò)事件的影響力、實時監(jiān)控網(wǎng)絡(luò)事件的發(fā)展規(guī)模和方向，預(yù)測預(yù)警級別，確定輿論引導的方向和措施，在網(wǎng)絡(luò)事件的發(fā)生初期進行引導，使其發(fā)展趨勢及影響力在可控制范圍內(nèi)。 本文基于遺傳算法設(shè)計網(wǎng)絡(luò)事件預(yù)測模型，在大數(shù)據(jù)環(huán)境下建立評價預(yù)測原型系統(tǒng)。對不同網(wǎng)絡(luò)事件在同一時間發(fā)展情況進行預(yù)測，得到良好的實驗結(jié)果，證明其使用價值與推廣價值 本文的主要創(chuàng)新點為： 1、發(fā)現(xiàn)黃金24小時為網(wǎng)絡(luò)事件早期和快速上升期的分界點規(guī)律；提出在黃金24小時實時發(fā)現(xiàn)評價、實時預(yù)測引導的網(wǎng)絡(luò)輿情監(jiān)控方法，從事件發(fā)展為熱點后的堵截轉(zhuǎn)變?yōu)樵缙诎l(fā)現(xiàn)預(yù)測和良性引導。 2、基于網(wǎng)絡(luò)事件內(nèi)容監(jiān)測和評論傾向性預(yù)測，建立自學習的網(wǎng)絡(luò)事件擴散模型；利用遺傳算法設(shè)計網(wǎng)絡(luò)事件預(yù)測算法和原型系統(tǒng)，具有計算簡單、處理時間快、自適應(yīng)及規(guī)模、范圍和態(tài)度控制的全面性等特點。
[Abstract]:With the arrival of big data 4G high-speed network era, real-time interaction, low-cost network events to social life, policies and regulations, people's mentality gradually deepened. Based on the early characteristics of network events, this paper carries out real-time monitoring and evaluation, and forecasts its future development in order to forewarn and guide the benign development of public opinion. This paper tracks and collects a large number of network events and records the early characteristics and final impact range, evaluates and evaluates the whole process, and summarizes the time law, heat law and biological clock law of network event diffusion. Different network event information screening rules and the same network event information screening rules. In this paper, the logical relationship between network event data is established by real-time network event classification, diffusion and tendency detection. According to the law of network event diffusion, the model of network event diffusion is established, the influence of network event is evaluated, the scale and direction of development of network event are monitored in real time, the warning level is predicted, and the direction and measures of public opinion guidance are determined. In the early stage of network events, the trend and influence of network events can be controlled. In this paper, a network event prediction model is designed based on genetic algorithm, and a prototype system of evaluation and prediction is established in big data environment. Different network events are predicted at the same time, and good experimental results are obtained. Prove its use value and popularize value The main innovations of this paper are: 1. It is found that gold is the dividing point between the early period of network event and the period of rapid rising in 24 hours. In this paper, a network public opinion monitoring method based on 24-hour real-time discovery evaluation and real-time prediction and guidance is proposed, which changes the interception from events to hot spots into early discovery, prediction and good guidance. 2. Based on the monitoring of network event content and the prediction of comment tendency, a self-learning model of network event diffusion is established. The genetic algorithm is used to design the network event prediction algorithm and the prototype system, which has the characteristics of simple calculation, fast processing time, adaptive and comprehensive control of scale, scope and attitude, etc.
【學位授予單位】：山東財經(jīng)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP18;TP393.06

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