自媒体时代的网络舆情传播机理、演化效应及引导策略研究

In the Era of Social Media, the transformation of information broadcasting patterns is affecting the whole process in which the impacts of online public opinions are made more extensive. Such new characteristics of public opinion broadcasting and evolution as being cross-regional, convert and complex have brought forth many challenges to studies on social governance. At present, studies on online public opinions in social media are being conducted from disperse perspectives and by adopting the unitary methodology. In the present research program, specific studies will be conducted in the following aspects from a cross-disciplinary perspective where both natural sciences and social sciences are taken in consideration and in both qualitative and quantitative manners: 1) to draw out a “Multidimensional Network Model” that is oriented at rules for the evolution and topology of facts on which public opinions are based, which has got the social dimension, the environmental dimension and the behavioral dimension integrated, based on the analyses about social media’s ecology of public opinion elements and by employing both socio-psychological and complicated networking methods; 2) to explore the rules for the broadcasting and evolution of the macroscopic state and the microscopic topic of public opinions in terms of orientation, heterization, and adhesion with a panorama view by means of mechanism analysis, algorithm design, analog verification and dynamic integrated simulation; 3) to build quantitative waveforms, net-form measuring indexes and mode identification algorithm and tap the combined guiding mechanism oriented at the whole lifecycle of public opinion evolution by use of such technologies as state forecasting and behavior mining. With the ecological system of public opinions on social media and multidimensional network models taken as the factual and structural basis, attention will not only be paid to new rules for the broadcasting and evolution of public opinions when carrying out the present research program but more importance will also be attached to the flexible guiding mechanism, which is of theoretic and immediate significance for both expanding studies on public opinions and the governance of network society.

自媒体时代，信息传播方式的转变影响着网络舆情整个发酵过程，其传播演化的超地域性、隐蔽性和复杂性等新特点给社会治理研究带来诸多挑战。目前自媒体舆情研究视角分散、方法单一，本课题从自然与社会交叉科学视角出发，定性定量相结合地开展以下研究：①以自媒体舆情要素生态系统分析为基础，结合社会心理学、复杂网络等方法，提出面向舆情事实演化拓扑结构，包含社交维、环境维和行为维的“多维网络模型”；②通过机理分析、算法设计、模拟验证、动态集成仿真等手段，全景式探究舆情宏观态势、微观话题传播演化的方向性、裂变性和粘合性规律；③构建定量化波形、网形测度指标及模式识别算法，借助态势预测、行为挖掘等技术，探索面向舆情演化全生命周期的组合式引导机制。本研究以自媒体舆情生态系统和多维网络模型为事实依据和结构基础，不仅关注舆情传播演化新规律，更强调其柔性引导机制，这对舆情拓展研究和网络社会治理具有重要理论和现实意义。

自媒体舆情传播演化的隐蔽性、动态性和复杂性，改变了传统“点到面”的传播路径，转化为“点到点”的对等传播方式，给社会治理研究带来诸多挑战。目前自媒体舆情研究视角分散、分析方法单一，本课题从自然与社会交叉科学视角出发，定性定量相结合地开展了以下研究：①以自媒体舆情要素作用机制分析为基础，结合社会心理学、复杂网络等方法，构建了面向舆情事实演化拓扑结构，包含社交维、环境维、行为维和心理维的“多维网络模型”；②通过机理分析、算法设计、模拟仿真等手段，全景式探究了舆情宏观发展扩散、微观异化耦合的规律性特征；③构建定量化的系统动力学模型，借助态势预测、行为挖掘等技术，探索了面向舆情演化全生命周期的组合式引导机制。上述研究进展的主要结论包括：①舆情发展前期、中期、后期的演化驱动力主要为舆论议题、舆论环境、网民心理等；②舆情异化极化过程受舆论内外部环境各种因素的多重影响，舆论环境、主体从众性加速了舆情话题的极化过程，高社会公信力可以降低舆情话题极化速度；③本研究提出的超边耦合算法具有82.22%的精确度，其中事件类型属性是舆情间是否发生耦合的主要影响因素，而心理属性、心理异化的影响机制相对复杂。④提高政府公信力、增加信息公开度，完善应急预案等宏观干预策略对传统媒体和网络新闻媒体的干预效果较为显著，隔离新闻、帖子、网民和话题等微观干预策略对各类媒介的干预效果均较为显著，但对自媒体舆情的干预效果最佳。本研究以微博数据为主，以微信公众号、贴吧、论坛数据等为补充，创新性地开展了全网环境下的自媒体舆情数据研究，研究过程以舆情生态关系和多维网络模型为事实依据和结构基础，不仅关注舆情传播演化新规律，更强调其组合引导机制，这对舆情拓展研究和网络社会治理具有重要理论和现实意义。基于项目主要结论，研究团队累计发表SCI、SSCI、CSSCI等核心期刊学术论文8篇，获批软件著作权2份、出版学术专著2部，110余份报告获得领导人重要批示，被决策部门采纳。