本文選題：網(wǎng)絡(luò)輿情 + 網(wǎng)絡(luò)輿情演變　； 參考：《南京理工大學(xué)》2017年碩士論文

【摘要】：隨著信息技術(shù)的快速發(fā)展,互聯(lián)網(wǎng)環(huán)境下的輿情問題被廣泛研究,學(xué)者們從不同視角取得了豐碩的研究成果,其中主要包括網(wǎng)絡(luò)輿情定義、成因、特征、演變以及輿情預(yù)警、預(yù)測(cè)等方面內(nèi)容。但就目前已有的研究成果來看,學(xué)者對(duì)于網(wǎng)絡(luò)輿情的討論通常都是將其視為單一事件在單一軌跡上的發(fā)展過程,對(duì)于原生輿情事件在不同因素影響下出現(xiàn)的后繼衍生輿情事件及多個(gè)輿情事件之間的關(guān)聯(lián)關(guān)系研究較少。網(wǎng)民因某些涉事主體、情緒或議題相似的多個(gè)事件而產(chǎn)生的情緒會(huì)彼此感染,當(dāng)相同或相似的情緒大量積累后,便會(huì)發(fā)生輿情共振現(xiàn)象。從現(xiàn)實(shí)生活中發(fā)生的事件來看,網(wǎng)絡(luò)輿情共振現(xiàn)象對(duì)社會(huì)造成的二次影響很可能比原來單一的網(wǎng)絡(luò)輿情事件造成的社會(huì)危害更大、破壞力更強(qiáng),造成1+12的后繼效應(yīng),因此加強(qiáng)網(wǎng)絡(luò)共振現(xiàn)象研究,對(duì)監(jiān)督社會(huì)情緒表達(dá)和網(wǎng)絡(luò)輿論具有重要的作用。雖然目前學(xué)者已經(jīng)展開了對(duì)于輿情共振現(xiàn)象的定性研究,但對(duì)于從微觀層面分析輿情共振規(guī)律的研究仍少之又少�；诖�,本文重點(diǎn)研究了網(wǎng)絡(luò)輿情原生事件與次生事件的共振現(xiàn)象,關(guān)注輿情共振過程中區(qū)域文化、人群特征、政府及網(wǎng)絡(luò)媒體介入等因素對(duì)輿情共振的影響。網(wǎng)絡(luò)輿情共振與物理共振十分相似,在網(wǎng)絡(luò)輿情中,各類信息分子不停地做無規(guī)則的運(yùn)動(dòng),受到輿情事件(如同花粉顆粒)不斷地隨機(jī)撞擊,使得輿情事件的話題隨機(jī)地向各個(gè)方向"游走",而隨機(jī)共振理論是朗之萬在研究布朗運(yùn)動(dòng)時(shí),建立的以微分方程為數(shù)學(xué)模型的理論基礎(chǔ);網(wǎng)絡(luò)輿情的發(fā)展趨勢(shì)通常為"起始-上漲-高潮-消退",類似于隨機(jī)共振理論所描述的雙穩(wěn)態(tài)系統(tǒng)的兩個(gè)勢(shì)阱與一個(gè)勢(shì)壘。因此,本文以物理學(xué)中隨機(jī)共振模型為理論基礎(chǔ),建立輿情共振方程,分析引發(fā)因素對(duì)輿情共振的影響,依托仿真實(shí)驗(yàn)探索輿情共振規(guī)律。仿真結(jié)果表明,不同區(qū)域不同議題網(wǎng)絡(luò)輿情共振的結(jié)果不同,并且意見領(lǐng)袖、執(zhí)法部門、當(dāng)事人、媒體的態(tài)度將會(huì)影響能否共振,以及共振的振幅。在理論研究的基礎(chǔ)上,本文采集了2013年乙肝疫苗事件及2016年山東疫苗事件在新浪微博上的真實(shí)數(shù)據(jù),對(duì)數(shù)據(jù)進(jìn)行處理、測(cè)算,據(jù)此對(duì)案例進(jìn)行分析,觀察本文推算結(jié)果是否與輿情事件在現(xiàn)實(shí)生活演變過程中出現(xiàn)的共振效應(yīng)相契合,以此來驗(yàn)證本文構(gòu)建的網(wǎng)絡(luò)輿情共振模型的合理性、實(shí)用性。結(jié)果顯示,本文提出的網(wǎng)絡(luò)輿情共振模型基本能夠描述現(xiàn)實(shí)社會(huì)中發(fā)生的網(wǎng)絡(luò)輿情共振現(xiàn)象規(guī)律。
[Abstract]:With the rapid development of information technology, the issue of public opinion in the Internet environment has been widely studied. Scholars have obtained fruitful research results from different perspectives, including the definition, causes, characteristics, evolution and early warning of public opinion. Prediction and other aspects. But as far as the existing research results are concerned, scholars' discussion of network public opinion is usually regarded as the development process of a single event on a single track. There is little research on the relationship between the derivative public opinion events and the multiple public opinion events under the influence of different factors. When the same or similar emotions accumulate, public opinion resonance will occur. From the point of view of the events in real life, the secondary influence of the phenomenon of network public opinion resonance on the society is likely to be greater and more destructive than the original single network public opinion event, resulting in a successor effect of 1 / 12. Therefore, strengthening the study of network resonance plays an important role in supervising social emotion expression and network public opinion. Although scholars have carried out qualitative research on the phenomenon of public opinion resonance, there are few researches on analyzing the law of public opinion resonance from the micro level. Based on this, this paper focuses on the resonance between primary and secondary events of network public opinion, and focuses on the influence of regional culture, crowd characteristics, government and network media intervention on public opinion resonance in the process of public opinion resonance. The network public opinion resonance is very similar to the physical resonance. In the network public opinion, all kinds of information molecules keep doing irregular movement, and they are hit by public opinion events (such as pollen grains) at random. It makes the topic of public opinion event "walk" to every direction at random, and the stochastic resonance theory is the theoretical foundation of Langevan's mathematical model based on differential equation when studying Brownian motion. The trend of network public opinion is usually "initial-upper-climax extinction", which is similar to two potential wells and one barrier of bistable system described by stochastic resonance theory. Therefore, based on the stochastic resonance model in physics, this paper establishes the equation of public opinion resonance, analyzes the influence of trigger factors on public opinion resonance, and explores the law of public opinion resonance based on simulation experiment. The simulation results show that the results of network public opinion resonance are different in different regions and different topics, and the attitude of opinion leaders, law enforcement agencies, parties and media will affect the resonance and the amplitude of the resonance. On the basis of theoretical research, this paper collected the real data of hepatitis B vaccine event in 2013 and Shandong vaccine event in 2016 on Sina Weibo, processed the data, calculated and analyzed the case. Whether the result of this paper is consistent with the resonance effect of public opinion event in the process of real life evolution is observed to verify the rationality and practicability of the network public opinion resonance model constructed in this paper. The results show that the network public opinion resonance model proposed in this paper can basically describe the phenomenon of network public opinion resonance in real society.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：C913.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 胡改麗;陳婷;陳福集;鄭小雪;;我國(guó)網(wǎng)絡(luò)輿情熱度分析文獻(xiàn)綜述[J];情報(bào)科學(xué);2016年01期

2 陳丹月;羅彬;;自媒體視域下微博與受眾情緒共振[J];新聞世界;2015年06期

3 郭穎旦;丁望峰;楊建宋;;朗之萬方程在布朗運(yùn)動(dòng)數(shù)值模擬中的時(shí)間尺度分析[J];杭州師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2015年02期

4 李倩倩;黃遠(yuǎn);姜景;沈乾;;中國(guó)網(wǎng)絡(luò)社會(huì)治理的輿論指數(shù)[J];中國(guó)科學(xué)院院刊;2015年01期

5 任立肖;張亮;杜子平;李楊;;復(fù)雜網(wǎng)絡(luò)上的網(wǎng)絡(luò)輿情演化模型研究述評(píng)[J];情報(bào)科學(xué);2014年08期

6 張偉;何明升;白淑英;金蕊;;基于Weisbuch-Deffuant模型的網(wǎng)絡(luò)輿論演化模式研究[J];情報(bào)雜志;2013年07期

7 甘旭升;崔浩林;吳亞榮;;基于功能共振事故模型的航空事故分析[J];中國(guó)安全科學(xué)學(xué)報(bào);2013年07期

8 孫帥;周毅;;2008-2012年國(guó)內(nèi)突發(fā)事件網(wǎng)絡(luò)輿情管理研究綜述[J];電子政務(wù);2013年05期

9 焦尚彬;何童;;基于雙穩(wěn)隨機(jī)共振的多頻弱信號(hào)檢測(cè)[J];計(jì)算機(jī)工程與應(yīng)用;2014年05期

10 陳桂茸;蔡皖東;徐會(huì)杰;晏沛湘;王劍平;;網(wǎng)絡(luò)輿論演化的高影響力優(yōu)先有限信任模型[J];上海交通大學(xué)學(xué)報(bào);2013年01期

相關(guān)博士學(xué)位論文 前1條

1 張靜;基于復(fù)雜網(wǎng)絡(luò)的微博用戶群體行為研究[D];北京郵電大學(xué);2015年

，

本文編號(hào)：1871011