scholarly journals Strategic Optimization of Public Opinion Management in Universities under Change of Network Public Opinion Ecosystem

2020 ◽  
Vol 4 (4) ◽  
pp. p28
Author(s):  
Shui Jingjing

The current breakthroughs in Internet big data and AI technologies have accelerated the fission-like dissemination of public opinion on the Internet, providing both opportunities and challenges for university governance. Universities should adapt to the new situation of the ecological change of public opinion with subject, object, carrier and environment as the elements, and optimize the public opinion management mechanism of universities from five levels: building a management system of network public opinion, strengthening the guidance mode of public opinion, promoting the operation of campus new media matrix, paying attention to the education of students’ network media literacy, and focusing on the construction of  open internal and external communication platform, purifying the network space, maintaining the image of universities, and creating a Double First-class construction of universities and necessary ecology.

Author(s):  
Yong Li ◽  
Xiaojun Yang ◽  
Min Zuo ◽  
Qingyu Jin ◽  
Haisheng Li ◽  
...  

The real-time and dissemination characteristics of network information make net-mediated public opinion become more and more important food safety early warning resources, but the data of petabyte (PB) scale growth also bring great difficulties to the research and judgment of network public opinion, especially how to extract the event role of network public opinion from these data and analyze the sentiment tendency of public opinion comment. First, this article takes the public opinion of food safety network as the research point, and a BLSTM-CRF model for automatically marking the role of event is proposed by combining BLSTM and conditional random field organically. Second, the Attention mechanism based on vocabulary in the field of food safety is introduced, the distance-related sequence semantic features are extracted by BLSTM, and the emotional classification of sequence semantic features is realized by using CNN. A kind of Att-BLSTM-CNN model for the analysis of public opinion and emotional tendency in the field of food safety is proposed. Finally, based on the time series, this article combines the role extraction of food safety events and the analysis of emotional tendency and constructs a net-mediated public opinion early warning model in the field of food safety according to the heat of the event and the emotional intensity of the public to food safety public opinion events.


Author(s):  
Douglas Foyle

Dramatic changes in the way the public acquires information and formulates its attitudes have potentially altered the opinion and foreign policy relationship. While traditional approaches have treated public opinion on domestic and foreign matters as largely distinct, the culmination of a series of changes may eliminate the effective distinction between foreign and domestic policy, at least in terms of how the American political system operates. All the factors central to the opinion and foreign policy process, such as information acquisition, attitude formation, media effects, the effect of opinion on policy, and presidential leadership now appear to mirror the processes observed at the domestic level. This analysis reviews historical trends in the literature on public opinion and foreign policy that has focused on the rationality of the public’s opinions, the structure of its attitudes, and its influence on foreign policymaking. The traditional Almond-Lippmann consensus portrayed an emotional public with unstructured attitudes and little influence on foreign policy; however, revisionist views have described a reasonable public with largely structured views on foreign policy that can, at times, constrain and even drive those policies. More recently, the rise of “intermestic” issues, contain both domestic and international elements, such as globalization, inequality, terrorism, immigration, and climate change, have interacted to transform the domestic and international context. The bulk of this analysis highlights emerging new research directions that should be pursued in light of the changes. First, scholars should continue to evaluate the “who thinks what and why” questions with particular attention to differences between high- and low-information individuals, the effect of misinformation, and information sources. In doing so, research should build on research from non-American contexts that points to the important influences of societal and institutional factors. In addition to continued examination of traditional demographic factors such as partisanship and ideology, additional attention should turn to consider potential genetic and biological foundations of attitudes. Finally, researchers should continue to evaluate how the new media environment, including social media, affects how the public accesses information, how the media provides information, and how political elites attempt to shape both. Given these changes, scholars should consider whether it continues to make sense to treat public opinion dynamics regarding foreign policy as distinct from domestic policy and its implications.


Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2921
Author(s):  
Xiaolin Li ◽  
Zhiyi Li ◽  
Yahe Tian

With the advent of the new media mobile Internet era, the network public opinion in colleges and universities, as an extension of social network public opinion, is also facing a crisis in the prevention, control, and governance system. In this paper, the Fiddler was used to collect the comments and other relevant data of the COVID-19 topic articles on the WeChat Official Accounts of China’s top ten universities in 2020. The BILSTM_LSTM sentiment analysis model was used to analyze the sentiment tendency of the comments, and the LDA topic model was used to mine the topics of the comments with different emotional attributes at different stages of COVID-19. Based on sentiment analysis and text mining, entities and relationships in the theme graph of public opinion events in colleges and universities were identified, and the Neo4j graph database was established to construct the sentimental knowledge graph of the pandemic theme of university public accounts. People’s attitudes in university public opinion are easily influenced by a variety of factors, and the degree of emotional disposition changes over time, with the stage the pandemic is in, and with different commentators; official account opinion topics change with the development of the time stage of the pandemic, and students’ positive and negative comment topics show a diverse trend. By incorporating topic mining into the sentimental knowledge graph, the graph can realize functions such as the emotion retrieval of comments on university public numbers, a source search of security threats in university social networks, and monitoring of comments on public opinion under the theme of the pandemic, which provides new ideas for further exploring the research and governance system of university network public opinion and is conducive to preventing and resolving campus public opinion crises.


2021 ◽  
Vol 2 (3) ◽  
pp. 126-128
Author(s):  
Xinhua Li ◽  
Zichen Li

Internet public opinion is an influential and tendentious opinion or speech expressed by the public on the Internet to a certain focus, which has formed a powerful force of public opinion. Internet public opinion has become a concentrated reflection of public opinion, opening up another channel to truly reflect public opinion, and effectively promoting the supervision of government officials and their decisions. In view of the strong emotional weakness of the current network public opinion, we can train forum opinion leaders to guide the public opinion with affinity and consideration, and select and enlarge the network public opinion by connecting the traditional media.


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