【摘要】：隨著互聯(lián)網(wǎng)時(shí)代的到來,網(wǎng)絡(luò)輿情已成為反映社情民意的晴雨表。作為近年來非常熱門的網(wǎng)絡(luò)社交平臺(tái)之一,微博以其傳播的及時(shí)性、內(nèi)容的自主性、互動(dòng)的友好性等優(yōu)勢(shì),不僅成為了廣大網(wǎng)民信息溝通和知識(shí)共享的平臺(tái),而且發(fā)展成網(wǎng)絡(luò)輿情的集散地。其中,“轉(zhuǎn)基因”一直是微博上熱門話題之一。轉(zhuǎn)基因技術(shù)作為一項(xiàng)新技術(shù)、新產(chǎn)業(yè),本身具有十分廣闊的發(fā)展前景。搶占轉(zhuǎn)基因技術(shù)制高點(diǎn)也是我國的科技發(fā)展戰(zhàn)略之一。但是目前我國轉(zhuǎn)基因領(lǐng)域的研究與推廣受限于諸多因素,其中最為突出的是公眾對(duì)轉(zhuǎn)基因安全問題的質(zhì)疑。許多網(wǎng)民通過微博參與轉(zhuǎn)基因的討論,而如今微博上的轉(zhuǎn)基因輿情也是如火如荼,因此探究微博轉(zhuǎn)基因輿情具有一定的意義。本文首先梳理了網(wǎng)絡(luò)輿情和微博輿情的相關(guān)文獻(xiàn),對(duì)比分析了國內(nèi)外的研究進(jìn)展和特點(diǎn),并據(jù)此提出幾點(diǎn)理論探索:(1)微博傳播是否符合復(fù)雜社會(huì)網(wǎng)絡(luò)的特性,(2)社會(huì)網(wǎng)絡(luò)分析方法能否反映微博輿情的特性,(3)社會(huì)網(wǎng)絡(luò)分析方法能否揭示微博輿情的演化;然后以轉(zhuǎn)基因網(wǎng)絡(luò)輿情為例,分析其現(xiàn)狀和特點(diǎn);再利用網(wǎng)絡(luò)爬蟲對(duì)新浪微博含有“轉(zhuǎn)基因”的微博進(jìn)行數(shù)據(jù)挖掘,采集得到從2009年8月到2014年底2700348條含有“轉(zhuǎn)基因”的微博;接著根據(jù)所得微博用戶數(shù)據(jù)構(gòu)建轉(zhuǎn)發(fā)關(guān)系網(wǎng)絡(luò),其中整個(gè)關(guān)系網(wǎng)絡(luò)有363640個(gè)微博用戶參與“轉(zhuǎn)基因”的轉(zhuǎn)發(fā),通過Pajek對(duì)轉(zhuǎn)發(fā)關(guān)系網(wǎng)絡(luò)進(jìn)行整體網(wǎng)絡(luò)分析、個(gè)體網(wǎng)絡(luò)分析和凝聚子群分析,并結(jié)合意見領(lǐng)袖的粉絲數(shù)、微博被轉(zhuǎn)發(fā)次數(shù)和日常活躍度,還有他們的微博認(rèn)證身份和對(duì)轉(zhuǎn)基因的態(tài)度,以及在不同時(shí)間節(jié)點(diǎn)上的發(fā)展變化,進(jìn)一步分析他們?cè)谵D(zhuǎn)基因輿情的傳播過程中的影響力和號(hào)召力;最后根據(jù)實(shí)證研究總結(jié)社會(huì)網(wǎng)絡(luò)分析方法在微博輿情傳播中的可用性。本文運(yùn)用社會(huì)網(wǎng)絡(luò)分析方法分析微博轉(zhuǎn)基因輿情,基于動(dòng)態(tài)的研究視角,通過提取微博意見領(lǐng)袖,最終得到以下結(jié)論:(1)微博輿情傳播符合復(fù)雜社會(huì)網(wǎng)絡(luò)的小世界和無標(biāo)度特性;(2)社會(huì)網(wǎng)絡(luò)分析方法可以反映微博輿情傳播的特性;(3)社會(huì)網(wǎng)絡(luò)分析方法能夠揭示微博輿情的演化。由此可知,在微博輿情的傳播過程中,通過構(gòu)建用戶的轉(zhuǎn)發(fā)關(guān)系網(wǎng)絡(luò)利用社會(huì)網(wǎng)絡(luò)分析的各項(xiàng)指標(biāo)不僅可以甄別出意見領(lǐng)袖,還可以發(fā)現(xiàn)近幾年他們?cè)谵D(zhuǎn)基因輿情的傳播過程中的發(fā)展變化。
[Abstract]:With the advent of the Internet era, network public opinion has become a barometer of social sentiment and public opinion. As one of the most popular online social platforms in recent years, Weibo has not only become a platform for information communication and knowledge sharing among Internet users because of its advantages of timeliness of communication, autonomy of content, and friendliness of interaction, etc. And to develop into the network of public opinion distribution center. Among them, "transgenic" has been one of the hot topics on Weibo. Transgenic technology as a new technology, new industry, itself has a very broad development prospects. Seizing the commanding height of GM technology is also one of our country's science and technology development strategies. However, the research and popularization of transgenic field in China is limited by many factors, the most prominent of which is the public's doubts about the safety of GM. Many netizens take part in the discussion of genetically modified genes through Weibo, and the public sentiment of the transgenic gene on Weibo is in full swing now, so it is of certain significance to explore the transgenic public opinion of Weibo. This article first combs the network public opinion and Weibo public opinion related literature, compares the domestic and foreign research progress and the characteristic, and then puts forward several theoretical exploration: (1) does Weibo communication accord with the complex social network characteristic, (2) can social network analysis method reflect the characteristics of Weibo's public opinion; (3) can social network analysis method reveal the evolution of Weibo's public opinion; Then take the transgenic network public opinion as an example, analyzes its present situation and the characteristic, then uses the network reptile to carry on the data mining to the Sina Weibo contain "transgenic" Weibo, gathers from August 2009 to the end of 2014 2700348 contains "genetically modified" Weibo; Then, according to the Weibo user data, the forwarding relationship network is constructed, in which 363640 Weibo users participate in the "transgenic" forwarding, and the overall network analysis of the forwarding relationship network is carried out through Pajek. Individual network analysis and aggregation subgroup analysis, combined with the number of followers of opinion leaders, Weibo's number of retweets and daily activity, as well as their Weibo authentication identity and attitude towards GM, as well as developments and changes at different time nodes. Further analysis of their influence and appeal in the process of GMO public opinion transmission; Finally, it summarizes the usability of social network analysis method in Weibo public opinion dissemination according to empirical research. This paper uses the social network analysis method to analyze Weibo transgenic public opinion, based on the dynamic research perspective, through the extraction of Weibo opinion leaders, Finally, the following conclusions are drawn: (1) the dissemination of public opinion of Weibo accords with the small-world and scale-free characteristics of complex social networks; (2) the social network analysis method can reflect the characteristics of Weibo's public opinion dissemination, (3) the social network analysis method can reveal the evolution of Weibo's public opinion. From this, we can see that in the process of spreading Weibo's public opinion, not only can the opinion leaders be identified by constructing the user's forwarding relationship network, but also by using the social network analysis indexes. They can also be found in recent years in the spread of genetically modified public opinion in the process of development.
【學(xué)位授予單位】：南京農(nóng)業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：G206

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 何建民;李雪;;面向微博輿情演化分析的隱馬爾科夫模型研究[J];情報(bào)科學(xué);2016年04期

2 翁士洪;張?jiān)?;公共議程設(shè)置中微博輿情互動(dòng)的社會(huì)網(wǎng)絡(luò)分析[J];武漢大學(xué)學(xué)報(bào)(人文科學(xué)版);2016年01期

3 高杰;楊劍;;論網(wǎng)絡(luò)輿情危機(jī)管理視域下政府形象的構(gòu)建——基于官員形象的反面案例分析[J];黨政干部論壇;2016年01期

4 杜楊沁;;政務(wù)微博整體網(wǎng)絡(luò)的關(guān)系解剖[J];現(xiàn)代情報(bào);2015年09期

5 全燕;;行走在“科學(xué)精神”和“社會(huì)契約”間的轉(zhuǎn)基因風(fēng)險(xiǎn)傳播[J];新聞界;2015年16期

6 蘇創(chuàng);彭錦;李圣國;;基于不確定微分方程的網(wǎng)絡(luò)輿情傳播模型研究[J];系統(tǒng)工程理論與實(shí)踐;2015年12期

7 ;兩會(huì):轉(zhuǎn)基因研究的“國家態(tài)度”引熱議[J];種業(yè)導(dǎo)刊;2015年04期

8 王晰巍;邢云菲;趙丹;李嘉興;;基于社會(huì)網(wǎng)絡(luò)分析的移動(dòng)環(huán)境下網(wǎng)絡(luò)輿情信息傳播研究——以新浪微博“霧霾”話題為例[J];圖書情報(bào)工作;2015年07期

9 楊輝;尚智叢;;微博科學(xué)傳播機(jī)制的社會(huì)網(wǎng)絡(luò)分析——以轉(zhuǎn)基因食品議題為例[J];科學(xué)學(xué)研究;2015年03期

10 朱毅華;張超群;;基于影響模型的網(wǎng)絡(luò)輿情演化與傳播仿真研究[J];情報(bào)雜志;2015年02期

相關(guān)博士學(xué)位論文 前4條

1 方潔;微博輿情利益相關(guān)者的分類及行為動(dòng)因研究[D];南京大學(xué);2014年

2 丁兆云;面向微博輿情的影響力分析關(guān)鍵技術(shù)研究[D];國防科學(xué)技術(shù)大學(xué);2013年

3 萬源;基于語義統(tǒng)計(jì)分析的網(wǎng)絡(luò)輿情挖掘技術(shù)研究[D];武漢理工大學(xué);2012年

4 王宇紅;我國轉(zhuǎn)基因食品安全政府規(guī)制研究[D];西北農(nóng)林科技大學(xué);2012年

相關(guān)碩士學(xué)位論文 前10條

1 米昂;結(jié)合影響力分析的微博輿情溯源研究[D];北京交通大學(xué);2015年

2 丁潔;基于社會(huì)網(wǎng)絡(luò)的網(wǎng)絡(luò)輿情演化研究[D];南京理工大學(xué);2015年

3 張東杰;名人微博輿論的傳播機(jī)制及其可視化研究[D];哈爾濱工業(yè)大學(xué);2014年

4 孫榮德;基于復(fù)合網(wǎng)的微博用戶行為特征研究[D];青島大學(xué);2014年

5 王愛玲;反腐類微博輿情熱點(diǎn)演化機(jī)制研究[D];山東大學(xué);2014年

6 余琪;政務(wù)微博中政府信息公開的效果評(píng)價(jià)研究[D];華中師范大學(xué);2014年

7 孫海燕;網(wǎng)絡(luò)輿情傳播模型研究[D];山東大學(xué);2014年

8 彭利斌;微博熱點(diǎn)話題發(fā)現(xiàn)與話題演化的研究[D];桂林電子科技大學(xué);2014年

9 任士偉;政府應(yīng)對(duì)網(wǎng)絡(luò)輿情的路徑研究[D];蘇州大學(xué);2014年

10 顧淑雯;基于社會(huì)網(wǎng)絡(luò)視角下的機(jī)構(gòu)投資者對(duì)公司治理效率的影響[D];上海交通大學(xué);2014年

，

本文編號(hào)：2411986