# Applications of Advanced Analysis Technologies in Precise Governance of Social Media Rumors
## 2 Literature Mining
### Summary of Literature Mining  
Through the summary of hot spots and trends of rumor research, it can be found that it is a trend to use advanced technologies such as machine learning to conduct research on rumors. In the current research, big data and advanced analysis technologies [23; 24; 25; 26; 60; 61; 62] are widely used in the recognition and detection of rumors, such as the machine learning methods in recent years. For example, CNN technology was originally used for image recognition and classification, but now it can be extended for rumor recognition and classification. RNN (recurrent neural network) has good performance in natural language processing (NLP) and time series prediction, so it can be used for rumor recognition and prediction. RF regression can be applied to select the key evaluation indexes. Rumor literature about rumors conducts theoretical and technical research from three research objects to provide support for rumor governance in general (as shown in Table 1):  
Rumor: Most papers study the rumors themselves (Research 1.1-3.3). The rumor diffusion model provides technical support for the characterization of the spread of rumors, and at the same time, it can determine which parameters in the model have significant effects on the spreading process. The detection of rumors also provides technical support for the governance of rumors. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{1}{c}{**Number**} & \multicolumn{1}{c}{**Categories**} & \multicolumn{1}{c}{**Research Directions, Technologies,**} & \multicolumn{1}{c}{**Research Object**} \\  & & & **and Representative Literature** & **Research Object** \\ \hline \multirow{2}{*}{6} & The generation of rumors & 6.1. & The psychology of rumors [4] & \\  & & 6.2. & Motivation and basic law of rumors [44; 45] & \\ \hline \multirow{2}{*}{7} & The social psychology of rumor spreading & 7.1. & Tension theory of cognitive dissonance [46] & \\  & & 7.2. & The theory based on collective memory and behavior [47] & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cont. Platform and agencies: Research 4.1-4.4 focus on existing rumor governance strategies of platforms and institutions or proposing feasible governance recommendations, which have positive support to rumor governance. Public: A part of the literature focuses on the public in the spread of rumors (Research 5.1-7.2). These papers study the role and influence of the public's psychology and behavior on the generation and dissemination of rumors, and also illustrate the influence of rumors on the public's psychology and behavior. Through systematic analysis of the rumor research literature, it can be seen that there is still development space in rumor governance. In terms of rumor governance and rumor control decision support, the big data generated by social media rumors in the new media era has not been really used. How to make good use of social media rumor big data and related analysis technologies to provide decision-making support for achieving rumor precise governance and improving the effectiveness of rumor governance also deserves more specific and in-depth exploration. (1) Few studies have integrated natural sciences and social sciences. Rumor governance is a multidisciplinary research field of psychology, sociology, communication, and management. After a long period of research, in terms of social sciences, qualitative research on dissemination of rumors and social psychology of diffusion has been profoundly accumulated. Although the research in natural sciences started late, in recent years, the research of rumor identification and rumor spreading simulation has progressed rapidly. At present, research in natural sciences and social sciences is relatively independent. In fact, taking the social psychology, mood, emotion, personality, attitude, and other characteristics of the rumor participants into account in rumor governance will help to classify the public so as to design a targeted anti-rumor strategy to break the dilemma of receiving refutation of false rumor.