scholarly journals Analysis of Public Opinion in Colleges and Universities Based on Wireless Web Crawler Technology in the Context of Artificial Intelligence

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
WenNing Wu ◽  
ZhengHong Deng
Keyword(s):  
Artificial Intelligence ◽  
Public Opinion ◽  
Colleges And Universities ◽  
Web Crawler ◽  
The Public ◽  
User Influence ◽  
Proposed Model ◽  
Wide Range ◽  
Different Dimensions ◽  
The Web

Wi-Fi-enabled information terminals have become enormously faster and more powerful because of this technology’s rapid advancement. As a result of this, the field of artificial intelligence (AI) was born. Artificial intelligence (AI) has been used in a wide range of societal contexts. It has had a significant impact on the realm of education. Using big data to support multistage views of every subject of opinion helps to recognize the unique characteristics of each aspect and improves social network governance’s suitability. As public opinion in colleges and universities becomes an increasingly important vehicle for expressing public opinion, this paper aims to explore the concepts of public opinion based on the web crawler and CNN (Convolutional Neural Network) model. Web crawler methodology is utilised to gather the data given by students of college and universities and mention them in different dimensions. This CNN has robust data analysis capability; this proposed model uses the CNN to analyse the public opinion. Preprocessing of data is done using the oversampling method to maximize the effect of classification. Through the association of descriptions, comprehensive utilization of image information like user influence, stances of comments, topics, time of comments, etc., to suggest guidance phenomenon for various schemes, helps to enhance the effectiveness and targeted social governance of networks. The overall experimentation was carried out in python here in which the suggested methodology was predicting the positive and negative opinion of the students over the web crawler technology with a low rate of error when compared to other existing methodology.

scholarly journals Corporate Governance of Artificial Intelligence in the Public Interest

Information ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 275
Author(s):  
Peter Cihon ◽  
Jonas Schuett ◽  
Seth D. Baum
Keyword(s):  
Artificial Intelligence ◽  
Corporate Governance ◽  
Law Enforcement ◽  
Nonprofit Organizations ◽  
Public Interest ◽  
Department Of Defense ◽  
The Public ◽  
Wide Range ◽  
The Media ◽  
The U.S

Corporations play a major role in artificial intelligence (AI) research, development, and deployment, with profound consequences for society. This paper surveys opportunities to improve how corporations govern their AI activities so as to better advance the public interest. The paper focuses on the roles of and opportunities for a wide range of actors inside the corporation—managers, workers, and investors—and outside the corporation—corporate partners and competitors, industry consortia, nonprofit organizations, the public, the media, and governments. Whereas prior work on multistakeholder AI governance has proposed dedicated institutions to bring together diverse actors and stakeholders, this paper explores the opportunities they have even in the absence of dedicated multistakeholder institutions. The paper illustrates these opportunities with many cases, including the participation of Google in the U.S. Department of Defense Project Maven; the publication of potentially harmful AI research by OpenAI, with input from the Partnership on AI; and the sale of facial recognition technology to law enforcement by corporations including Amazon, IBM, and Microsoft. These and other cases demonstrate the wide range of mechanisms to advance AI corporate governance in the public interest, especially when diverse actors work together.

Analysis of Public Sentiments About Mega Online Sale Using Tweets on Big Billions Day Sale

2019 ◽  
pp. 59-76 ◽  
Author(s):  
Dilip Singh Sisodia ◽  
Ritvika Reddy
Keyword(s):  
Social Networking ◽  
Sentiment Analysis ◽  
Stock Exchange ◽  
The Public ◽  
Online Sales ◽  
Public Sentiment ◽  
Online Platforms ◽  
Wide Range ◽  
Automated Process ◽  
The Web

The opinion of others significantly influences our decision-making process about any product or service. The positive or negative opinions of prospective clients or customers may promote or demote the profit margin of any business activities. Therefore, analyzing the public sentiment is important for many applications such as firms trying to find out the response of their products in the market, predicting political elections, and predicting socioeconomic phenomena such as stock exchange, sale of products, etc. With the emergence of Web 2.0 services, a wide range of online platforms including micro-blogging, social networking, and many other review platforms are available. The automated process for public sentiment analysis from a large amount of social data present on the web helps to improve customer satisfaction. This chapter discusses the process of sentiment analysis of prospective buyers of mega online sales using their posted tweets about the big billions day sale.

The cooperative and competitive mechanisms of a leader’s opinion transmission

2020 ◽  
Vol 31 (09) ◽  
pp. 2050127
Author(s):  
Adil Amirjanov
Keyword(s):  
Public Opinion ◽  
Numerical Experiments ◽  
Continuous Model ◽  
Opinion Formation ◽  
Agent Based ◽  
The Public ◽  
Proposed Model ◽  
Cooperative Process ◽  
Competitive Mechanisms ◽  
The Individual

The paper modeled a leader’s opinion transmission in a population. The proposed model develops the cooperation agent-based continuous model in which the cooperation of individuals is based on the similarity of evolved “tags” which are relative to evolved tag-difference tolerances. In proposed model, an individual’s opinion and the individual’s tolerance are specified as variables in the model. During communication with each other and with a leader, the resources of individuals are incremented, if they are tolerable to the opinions of their opponents. An opinion formation in population is established by a cooperative process — changing individual’s opinion, if the individual is tolerable to the opinions of opponents, and by a competitive process — copying opinions and tolerances of successful individuals who have higher resource. Numerical experiments have proven that the public opinion reached a consensus followed the leader’s opinion.

scholarly journals Globalisation Scepticism in the Visegrad Countries

2021 ◽  
Vol 50 (4) ◽  
pp. 429-451
Author(s):  
Marianna Dudášová
Keyword(s):  
Public Opinion ◽  
European Integration ◽  
The European Union ◽  
The Public ◽  
Parallel Processes ◽  
Recent Developments ◽  
Different Dimensions ◽  
Visegrad Group ◽  
Visegrád Countries ◽  
The Eu

Recent developments in the European Union revealed significant differences between the Visegrad countries and the remaining members of the EU. The enlargement euphoria of the first decade of the 21st century was replaced by certain enlargement fatigue, manifesting itself not only in concrete governmental policies but also in the public opinion towards the EU. As European integration and globalisation are parallel processes, declining support for European integration must not necessarily be the result of disagreement with specific policies and should be examined in the broader context of globalisation fears and anxieties. The article describes variations in globalisation scepticism between the group of Visegrad countries and the remaining countries of the EU as well as variations within the Visegrad group itself, focusing on the main drivers of economic globalisation – international trade, foreign direct investment, and immigration. The development of public opinion since the financial and economic crisis in 2009 indicates that Visegrad countries should not be treated as a uniform bloc of globalisation sceptics as there are significant differences in opinion between the more pessimistic Czechs and Slovaks and the more optimistic Poles and Hungarians. Their globalisation scepticism also varies across different dimensions of globalisation and is fuelled by different motivations.

scholarly journals COVID-19 Vaccine and Social Media in the U.S.: Exploring Emotions and Discussions on Twitter

Vaccines ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1059
Author(s):  
Amir Karami ◽  
Michael Zhu ◽  
Bailey Goldschmidt ◽  
Hannah R. Boyajieff ◽  
Mahdi M. Najafabadi
Keyword(s):  
Public Opinion ◽  
Statistical Tests ◽  
Small Scale ◽  
Success Factor ◽  
Great Opportunity ◽  
Public Response ◽  
The Public ◽  
Wide Range ◽  
Significant Difference ◽  
Negative Sentiment

The understanding of the public response to COVID-19 vaccines is the key success factor to control the COVID-19 pandemic. To understand the public response, there is a need to explore public opinion. Traditional surveys are expensive and time-consuming, address limited health topics, and obtain small-scale data. Twitter can provide a great opportunity to understand public opinion regarding COVID-19 vaccines. The current study proposes an approach using computational and human coding methods to collect and analyze a large number of tweets to provide a wider perspective on the COVID-19 vaccine. This study identifies the sentiment of tweets using a machine learning rule-based approach, discovers major topics, explores temporal trend and compares topics of negative and non-negative tweets using statistical tests, and discloses top topics of tweets having negative and non-negative sentiment. Our findings show that the negative sentiment regarding the COVID-19 vaccine had a decreasing trend between November 2020 and February 2021. We found Twitter users have discussed a wide range of topics from vaccination sites to the 2020 U.S. election between November 2020 and February 2021. The findings show that there was a significant difference between tweets having negative and non-negative sentiment regarding the weight of most topics. Our results also indicate that the negative and non-negative tweets had different topic priorities and focuses. This research illustrates that Twitter data can be used to explore public opinion regarding the COVID-19 vaccine.

The Research on Dynamics Evolution Patterns of Online Public Opinion

2013 ◽  
Vol 411-414 ◽  
pp. 186-191
Author(s):  
Jin Du ◽  
Yan Hui Du ◽  
Yu Chen
Keyword(s):  
Artificial Intelligence ◽  
Public Opinion ◽  
Social Network ◽  
The Public ◽  
Network Cluster ◽  
Correlation Degree ◽  
General Rules ◽  
Control Pattern ◽  
Relationship Of ◽  
The Relationship

Dynamics evolution patterns play an important role on Public opinion nowadays. In this paper, developing rules and trends are discussed by means of Petri method of online public opinion. The public opinion online was analyzed as a stream from which the conception of public opinion stream was proposed and its control pattern was developed as well. Based on these, correlation degree variables between social network cluster nodes were dynamically introduced, and general rules of public opinion streams between associated network cluster organizations were studied. The Public-opinion-stream correlation control pattern which can regulate the relationship of social network cluster nodes and verify the empirical research of sociology, journalism and psychology. At last, artificial intelligence and decision support can be supplied to relevant industries by instructing system design and management system.

Analysis and Management of Flu Disease Public Opinion Based on Machine Learning

2021 ◽  
Vol 11 (7) ◽  
pp. 1791-1797
Author(s):  
Jie Zhang ◽  
Chao Yuan
Keyword(s):  
Public Opinion ◽  
New Media ◽  
Early Warning ◽  
Information Dissemination ◽  
Improved Genetic Algorithm ◽  
The Public ◽  
Wide Range ◽  
Short Time ◽  
Information Publishing ◽  
Transmission Speed

In the new media era, there are more ways of information dissemination, and the speed of information dissemination becomes faster. Along with it, various public opinions and rumors flood the cyberspace. As a mainstream social media information publishing platform, microblog has become the main way for netizens to obtain, disseminate and publish information. Because microblog can freely make speeches, and has a fast transmission speed and a wide range, it is easy for public opinion information to be widely disseminated in a short time. In particular, information such as rumors in public opinion can affect the network environment and social stability. Therefore, it is necessary to analyze and predict public opinion changes and to provide early warning. The literature uses the classic BP-NN (BP-NN) as the base prediction model, and uses the information published on the Sina microblog platform as a sample to analyze and predict the public opinion of influenza diseases. Due to the BP-NN’ slow convergence speed, this paper introduces an improved genetic algorithm to select the optimal parameters in the BP-NN (IGA-BP-NN), shorten the calculation time, and improve the analysis and prediction efficiency. The experiments verify that the work in this paper can provide more accurate early-warning information for the public opinion management of related departments.

scholarly journals Learning to Crawl

2020 ◽  
Vol 34 (04) ◽  
pp. 6046-6053
Author(s):  
Utkarsh Upadhyay ◽  
Robert Busa-Fekete ◽  
Wojciech Kotlowski ◽  
David Pal ◽  
Balazs Szorenyi
Keyword(s):  
Simulation Study ◽  
Optimization Problem ◽  
A Priori ◽  
Web Crawler ◽  
Natural Restriction ◽  
Partial Observations ◽  
Elapsed Time ◽  
Wide Range ◽  
Point Of Departure ◽  
The Web

Web crawling is the problem of keeping a cache of webpages fresh, i.e., having the most recent copy available when a page is requested. This problem is usually coupled with the natural restriction that the bandwidth available to the web crawler is limited. The corresponding optimization problem was solved optimally by Azar et al. (2018) under the assumption that, for each webpage, both the elapsed time between two changes and the elapsed time between two requests follows a Poisson distribution with known parameters. In this paper, we study the same control problem but under the assumption that the change rates are unknown a priori, and thus we need to estimate them in an online fashion using only partial observations (i.e., single-bit signals indicating whether the page has changed since the last refresh). As a point of departure, we characterise the conditions under which one can solve the problem with such partial observability. Next, we propose a practical estimator and compute confidence intervals for it in terms of the elapsed time between the observations. Finally, we show that the explore-and-commit algorithm achieves an O(√T) regret with a carefully chosen exploration horizon. Our simulation study shows that our online policy scales well and achieves close to optimal performance for a wide range of parameters.

Addresses by Elihu Root on International Subjects

1918 ◽  
Vol 12 (1) ◽  
pp. 15-26
Author(s):  
Charlemagne Tower
Keyword(s):  
Public Opinion ◽  
Public Interest ◽  
Panama Canal ◽  
Public Attention ◽  
Monroe Doctrine ◽  
The Public ◽  
Wide Range ◽  
First Impression ◽  
The Hague ◽  
International Thought

The first impression that we obtain upon opening this book is one rather of surprise at the extraordinarily wide range of subjects which Mr. Root has treated in the course of his addresses and speeches on international questions, to which the volume is confined, — a range that covers the ground and sets forth the essential facts as well as the arguments which have served to build up American public opinion and to direct the international thought of this country for almost a generation. The relations with Japan, the Panama Canal, the Conferences at The Hague, the rights and duties of nations, and the protection of citizens residing abroad, have filled a large part of public attention during the last quarter of a century; indeed, some of the questions included here, like the intercourse with Mexico and the Monroe Doctrine, have held the public interest since long before our own time.

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