Modelling the dynamic emotional information propagation and guiding the public sentiment in the Chinese Sina-microblog

Abstract This article compares the public perceptions of various types of migrants in Japan and examines whether Japanese view them equally. Using an original survey, which presented six types of migrants that Japanese people most commonly face in their daily lives, I show several interesting results. First, respondents express the most negative views toward labor migrants. Second, respondents who have migrant friends tend to have more positive feelings for all types of migrants. In contrast, simple coexistence with migrants fails to enhance public sentiment toward labor migrants, particularly those whose stay is temporary. Overall, my statistical results suggest that Japanese people are not pessimistic about every kind of migrant, and their openness increases as migrants acculturate into Japanese society and interact with Japanese people. These findings provide evidence to influence policy discussions on whether Japan should recruit labor migrants in its current form in order to fight its aging population.

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MoSa: A Modeling and Sentiment Analysis System for Mobile Application Big Data

Symmetry ◽

10.3390/sym11010115 ◽

2019 ◽

Vol 11 (1) ◽

pp. 115 ◽

Cited By ~ 2

Author(s):

Yaocheng Zhang ◽

Wei Ren ◽

Tianqing Zhu ◽

Ehoche Faith

Keyword(s):

Sentiment Analysis ◽

Interaction Design ◽

Mobile Application ◽

Situational Awareness ◽

Mobile Internet ◽

The Public ◽

Public Sentiment ◽

High Altitude Area ◽

Sentiment Dictionary ◽

Analysis System

The development of mobile internet has led to a massive amount of data being generated from mobile devices daily, which has become a source for analyzing human behavior and trends in public sentiment. In this paper, we build a system called MoSa (Mobile Sentiment analysis) to analyze this data. In this system, sentiment analysis is used to analyze news comments on the THAAD (Terminal High Altitude Area Defense) event from Toutiao by employing algorithms to calculate the sentiment value of the comment. This paper is based on HowNet; after the comparison of different sentiment dictionaries, we discover that the method proposed in this paper, which use a mixed sentiment dictionary, has a higher accuracy rate in its analysis of comment sentiment tendency. We then statistically analyze the relevant attributes of the comments and their sentiment values and discover that the standard deviation of the comments’ sentiment value can quickly reflect sentiment changes among the public. Besides that, we also derive some special models from the data that can reflect some specific characteristics. We find that the intrinsic characteristics of situational awareness have implicit symmetry. By using our system, people can obtain some practical results to guide interaction design in applications including mobile Internet, social networks, and blockchain based crowdsourcing.

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Has Anyone Seen It?

East European Politics and Societies and Cultures ◽

10.1177/0888325411398909 ◽

2012 ◽

Vol 26 (1) ◽

pp. 189-212 ◽

Cited By ~ 1

Author(s):

Dagmar Radin ◽

Aleksandar Džakula

Keyword(s):

Health Care ◽

Public Opinion ◽

Parliamentary Elections ◽

Political Actors ◽

The Public ◽

Public Sentiment ◽

Public Opinion Surveys ◽

Health Care Performance ◽

Policy Arena ◽

Care Performance

Over the past decade, public opinion surveys have shown that Croats are deeply dissatisfied with their health care system and asses it to be one of the most important issues. However, health care hardly makes it into any political discourse in Croatia. This study analyzes the results of a public opinion survey conducted before the 2007 parliamentary elections to find out what the public sentiment on health care performance in Croatia is and to analyze the reasons why health care is not addressed by political actors. Evidence suggests that while health care is the most salient issue today, the public often understands it poorly. Thus, in a political environment of competing issues, and given the complexity of tacking health care in the policy arena, politicians strategically avoid discussing the issue.

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Opinion Mining and Sentiment Analysis on Big Data

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit2063100 ◽

2020 ◽

pp. 410-415

Author(s):

Shruti Rajkumar Choudhary

Keyword(s):

Artificial Intelligence ◽

Social Networking ◽

Sentiment Analysis ◽

Text Analysis ◽

Opinion Mining ◽

Stock Exchange ◽

Daily Basis ◽

Text Data ◽

The Public ◽

Public Sentiment

<p>Opinion mining is extract subjective information from text data using tools such as NLP, text analysis etc. Automated opinion mining often uses machine learning, a type of artificial intelligence (AI), to mine text for sentiment. Opinion mining, which is also called sentiment analysis, involves building a system to collect and categorize opinions about a product.In this project the problem of sentiment analysis in twitter; that is classifying tweets according to the sentiment expressed in terms of positive, negative or neutral. Twitter is an online micro-blogging and social-networking platform which allows users to write short status updates of maximum length 140 characters. It is a rapidly expanding service with over 200 million registered users out of which 100 million are active users and half of them log on twitter on a daily basis - generating nearly 250 million tweets per day. Due to this large amount of usage we hope to achieve a reflection of public sentiment by analysing the sentiments expressed in the tweets. Analysing 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 like stock exchange.</p>

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Revealing public opinion towards COVID-19 vaccines with Twitter data in the United States: a spatiotemporal perspective (Preprint)

10.2196/preprints.30854 ◽

2021 ◽

Author(s):

Tao Hu ◽

Siqin Wang ◽

Wei Luo ◽

Mengxi Zhang ◽

Xiao Huang ◽

...

Keyword(s):

Public Health ◽

Public Opinion ◽

Public Attitudes ◽

The United States ◽

Health Crisis ◽

The Public ◽

Public Sentiment ◽

Spatiotemporal Trends ◽

The Us ◽

Key Events

BACKGROUND The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the US and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance OBJECTIVE The aim of this study is to investigate public opinion and perception on COVID-19 vaccines by investigating the spatiotemporal trends of their sentiment and emotion towards vaccines, as well as how such trends relate to popular topics on Twitter in the US METHODS We collected over 300,000 geotagged tweets in the US from March 1, 2020 to February 28, 2021. We examined the spatiotemporal patterns of public sentiment and emotion over time at both national and state scales and identified three phases along the pandemic timeline with the significant changes of public sentiment and emotion, further linking to eleven key events and major topics as the potential drivers to induce such changes via cloud mapping of keywords and topic modelling RESULTS An increasing trend of positive sentiment in parallel with the decrease of negative sentiment are generally observed in most states, reflecting the rising confidence and anticipation of the public towards vaccines. The overall tendency of the eight types of emotion implies the trustiness and anticipation of the public to vaccination, accompanied by the mixture of fear, sadness and anger. Critical social/international events and/or the announcements of political leaders and authorities may have potential impacts on the public opinion on vaccines. These factors, along with important topics and manual reading of popular posts on eleven key events, help identify underlying themes and validate insights from the analysis CONCLUSIONS The analyses of near real-time social media big data benefit public health authorities by enabling them to monitor public attitudes and opinions towards vaccine-related information in a geo-aware manner, address the concerns of vaccine skeptics and promote the confidence of individuals within a certain region or community, towards vaccines

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Ichiro the Public Diplomat: Professional Sport as Cultural Intermediary in Configuring US-Japan Relations

The Hague Journal of Diplomacy ◽

10.1163/1871191x-bja10007 ◽

2021 ◽

Vol 16 (1) ◽

pp. 82-104

Author(s):

Derek Moscato

Keyword(s):

Soft Power ◽

Public Diplomacy ◽

The United States ◽

Professional Baseball ◽

Policy Issues ◽

The Public ◽

Global Engagement ◽

Public Sentiment ◽

Survey Responses

Summary This study examines the confluence of sport and soft power within public diplomacy. It analyses professional baseball player Ichiro Suzuki’s role in the United States as a sporting ambassador from Japan — potentially catalysing goodwill, cultural interest, perceptions of national personality traits and even views of policy issues such as international trade and country relations. In doing so, this research draws from non-state public diplomacy, which considers the transnational impacts of non-traditional communication vehicles such as cultural and sporting exchanges. It measures US public sentiment towards Japan through quantitative analysis of survey responses collected by Pew Research Center in conjunction with the Sasakawa Peace Foundation. The success of Japan’s cultural and sporting exports highlights their potential and realised role in binding national ties. Furthermore, Tokyo’s hosting of the Summer Olympiad emphasises the role of sport not only as a vehicle for competition and entertainment but also its utility in global engagement.

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

Advances in Business Information Systems and Analytics - Sentiment Analysis and Knowledge Discovery in Contemporary Business ◽

10.4018/978-1-5225-4999-4.ch005 ◽

2019 ◽

pp. 59-76 ◽

Cited By ~ 2

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.

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Interpreting the Public Sentiment Variations on Twitter

IEEE Transactions on Knowledge and Data Engineering ◽

10.1109/tkde.2013.116 ◽

2014 ◽

Vol 26 (5) ◽

pp. 1158-1170 ◽

Cited By ~ 47

Author(s):

Shulong Tan ◽

Yang Li ◽

Huan Sun ◽

Ziyu Guan ◽

Xifeng Yan ◽

...

Keyword(s):

The Public ◽

Public Sentiment

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Perceptions About Sexual Offenses: Misconceptions, Punitiveness, and Public Sentiment

Criminal Justice Policy Review ◽

10.1177/0887403416660150 ◽

2016 ◽

Vol 30 (2) ◽

pp. 254-273 ◽

Cited By ~ 7

Author(s):

Laura L. King

Keyword(s):

Public Opinion ◽

Sex Offenders ◽

Sexual Offending ◽

Punitive Attitudes ◽

The Public ◽

Sexual Offenses ◽

Public Sentiment ◽

High Level

Decades of research on public opinion about crime reveal varying, yet relatively punitive attitudes that are often riddled with misconceptions. Sparked by the increased media and legislative attention devoted to sex offenders beginning in the 1990s, researchers began to more closely examine public opinion about sexual offenses. Findings suggest the public adheres to several misconceptions about sexual offenses and supports harsh sanctions for offenders. However, further research is warranted to more closely examine the relationships among these variables. Thus, the goal of the present study was to survey Pennsylvania residents to examine the degree to which misconceptions about sexual offenses inform punitiveness. The results supported the hypotheses in that a high level of support for misconceptions and punitiveness was identified, and adherence to misconceptions was the strongest predictor of punitiveness. These findings demonstrate a clear need for educational and awareness efforts to dispel public misconceptions about sexual offending and victimization.

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