【摘要】：隨著4G網(wǎng)絡(luò)的發(fā)展及移動(dòng)終端的普及,公眾表達(dá)情緒、發(fā)表觀點(diǎn)的方式由傳統(tǒng)信息媒介轉(zhuǎn)移到多媒體互聯(lián)網(wǎng)平臺(tái)上,促使多媒體網(wǎng)絡(luò)輿情信息傳播走進(jìn)公眾視野。公眾通過APP軟件、智能手機(jī)、各類移動(dòng)終端便攜、快速的參與到微博、微信、論壇等媒介承載的網(wǎng)絡(luò)輿情信息中。與傳統(tǒng)的報(bào)紙、電視等媒體相比較,多媒體網(wǎng)絡(luò)輿情具有傳播速度快、信息數(shù)量龐大、存儲(chǔ)、管理、分析困難,輿情危機(jī)形成概率高,影響范圍廣,影響力強(qiáng)等特點(diǎn)。一旦形成輿情危機(jī),損失不可估量。有關(guān)部門將多媒體網(wǎng)絡(luò)輿情危機(jī)的及時(shí)監(jiān)測與分析,作為引導(dǎo)、疏導(dǎo)輿情危機(jī)的先決條件。指標(biāo)體系的構(gòu)建正是危機(jī)監(jiān)測的基礎(chǔ)和依據(jù)。本文旨在構(gòu)建多媒體網(wǎng)絡(luò)輿情危機(jī)監(jiān)測指標(biāo)體系。首先,在研究多媒體網(wǎng)絡(luò)輿情傳播過程、分析影響輿情演進(jìn)要素的基礎(chǔ)上,本文提煉涵蓋輿情產(chǎn)生發(fā)展的5個(gè)要素(輿情主體、輿情客體、輿情本體,輿情媒介、輿情環(huán)境)作為指標(biāo)體系中的一級(jí)指標(biāo),同時(shí)在研究國內(nèi)外文獻(xiàn)及權(quán)威機(jī)構(gòu)指標(biāo)體系,建立了二級(jí)指標(biāo),并給出可量化的末級(jí)指標(biāo)。整個(gè)指標(biāo)體系客觀性較強(qiáng),具有廣泛的代表性;其次,針對(duì)現(xiàn)有多媒體網(wǎng)絡(luò)輿情信息量龐大的特點(diǎn),本文利用Hadoop大數(shù)據(jù)處理平臺(tái),利用聚類,分類,關(guān)聯(lián)規(guī)則等數(shù)據(jù)挖掘技術(shù)進(jìn)行動(dòng)態(tài)數(shù)據(jù)采集,快速處理圖片、文本、視頻等半結(jié)構(gòu)化、結(jié)構(gòu)化、非結(jié)構(gòu)化的數(shù)據(jù),為多媒體網(wǎng)絡(luò)輿情危機(jī)的實(shí)時(shí)監(jiān)測提供思路;再次,對(duì)指標(biāo)進(jìn)行篩選,采用相關(guān)性分析、主成分分析相結(jié)合的方法。先利用相關(guān)性分析方法,除去同一層指標(biāo)集內(nèi)相關(guān)系數(shù)較大的指標(biāo),確保剩余的指標(biāo)體系能夠表征初始指標(biāo)集信息,降低初始指標(biāo)集的冗余程度,之后再采用主成分分析法,通過線性變換,將剩余指標(biāo)集進(jìn)行降維處理,并借助累計(jì)方差貢獻(xiàn)率思想驗(yàn)證最終的指標(biāo)體系冗余度較低且信息表征能力依然很強(qiáng);最后,采用基于遺傳算法的BP神經(jīng)網(wǎng)絡(luò)確定篩選后各級(jí)指標(biāo)的權(quán)重,利用德爾菲法與SPSS分析相結(jié)合方法設(shè)定初始控制參數(shù)及輿情危機(jī)等級(jí),在降低人為主觀因素影響評(píng)價(jià)結(jié)果的基礎(chǔ)上,在宏觀上映射出指標(biāo)體系重要性,在微觀上展示確定指標(biāo)權(quán)值的客觀性。本文以“韓國薩德”事件為實(shí)例模型,驗(yàn)證本文構(gòu)建的多媒體網(wǎng)絡(luò)輿情危機(jī)監(jiān)測指標(biāo)體系的合理性及必要性。
[Abstract]:With the development of 4G network and the popularity of mobile terminals, the way of public expression and expression of opinions is transferred from traditional information media to multimedia Internet platform, which promotes the dissemination of multimedia network public opinion information into the public view. Through app software, smart phone, various mobile terminals portable, the public quickly participate in Weibo, WeChat, forum and other media to carry network public opinion information. Compared with the traditional media such as newspapers and TV, multimedia network public opinion has the characteristics of rapid transmission, large amount of information, storage, management, analysis difficulties, high probability of public opinion crisis formation, wide range of influence, strong influence and so on. Once the public opinion crisis, the loss is incalculable. Relevant departments take the timely monitoring and analysis of multimedia network public opinion crisis as a prerequisite for guiding and unblocking public opinion crisis. The construction of index system is the foundation and basis of crisis monitoring. The purpose of this paper is to construct a multi-media network public opinion crisis monitoring index system. First of all, on the basis of studying the transmission process of multimedia network public opinion and analyzing the factors influencing the evolution of public opinion, this paper abstracts five elements (public opinion subject, public opinion object, public opinion ontology, public opinion medium) that cover the generation and development of public opinion. The environment of public opinion) is the first class index in the index system. At the same time, the index system of domestic and foreign literature and authoritative organizations is studied, the secondary index is established, and the final quantifiable index is given. The whole index system has strong objectivity and extensive representativeness. Secondly, in view of the huge amount of multimedia network public opinion information, this paper uses Hadoop big data processing platform, using clustering, classification, Association rules and other data mining technology for dynamic data acquisition, fast processing of images, text, video and other semi-structured, unstructured data, for multimedia network public opinion crisis real-time monitoring ideas; third, The method of combining correlation analysis and principal component analysis was used to screen the indicators. Firstly, the correlation analysis method is used to remove the index with large correlation coefficient in the same index set, to ensure that the remaining index system can represent the information of the initial index set and reduce the redundancy degree of the initial index set, then the principal component analysis method is used. Through the linear transformation, the residual index set is reduced, and the contribution rate of cumulative variance is used to verify that the redundancy of the final index system is low and the information representation ability is still very strong. BP neural network based on genetic algorithm is used to determine the weight of every index after screening, and the initial control parameters and public opinion crisis level are set by combining Delphi method and SPSS analysis. On the basis of reducing the impact of human subjective factors on the evaluation results, the importance of index system is mapped out in macro level, and the objectivity of determining index weights is shown in micro level. Taking the case model of "Korea sad" as an example, this paper verifies the rationality and necessity of the multi-media network public opinion crisis monitoring index system constructed in this paper.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：G206

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本文編號(hào)：2135872