Do mass media influence people's opinion of other countries? Using BERT, a deep neural network-based natural language processing model, we analyze a large corpus of 267,907 China-related articles published by The New York Times since 1970. We then compare our output from The New York Times to a longitudinal data set constructed from 101 cross-sectional surveys of the American public's views on China. We find that the reporting of The New York Times on China in one year explains 54% of the variance in American public opinion on China in the next. Our result confirms hypothesized links between media and public opinion and helps shed light on how mass media can influence public opinion of foreign countries.
University of Jinan（济南大学）；University of Chinese Academy of Sciences（中国科学院大学）；Chinese Academy of Sciences（中国科学院）；Shaanxi Normal University（陕西师范大学）；Shihezi University（石河子大学）；Shanghai Institute of Technology（上海应用技术大学）
The Internet contains a wealth of public opinion on food safety, including views on food adulteration, food-borne diseases, agricultural pollution, irregular food distribution, and food production issues. In order to systematically collect and analyse public opinion on food safety, we developed IFoodCloud, a platform for the real-time sentiment analysis of public opinion on food safety in China. It collects data from more than 3,100 public sources that can be used to explore public opinion trends, public sentiment, and regional attention differences of food safety incidents. At the same time, …
Nanjing University of Science and Technology（南京理工大学）；Alibaba Research Center for Complex Sciences, Hangzhou Normal University（杭州师范大学阿里巴巴复杂科学研究中心）；Hangzhou Normal University（杭州师范大学）；Jiangsu Key Laboratory of Data Engineering and Knowledge Service, Nanjing University（南京大学江苏省数据工程与知识服务重点实验室）；Nanjing University（南京大学）
With the development of e-commerce, many products are now being sold worldwide, and manufacturers are eager to obtain a better understanding of customer behavior in various regions. To achieve this goal, most previous efforts have focused mainly on questionnaires, which are time-consuming and costly. The tremendous volume of product reviews on e-commerce websites has seen a new trend emerge, whereby manufacturers attempt to understand user preferences by analyzing online reviews. Following this trend, this paper addresses the problem of studying customer behavior by exploiting recently develop…
Massachusetts Institute of Technology（麻省理工学院）；Google（谷歌）；Harvard University（哈佛大学）
Public opinion reflects and shapes societal behavior, but the traditional survey-based tools to measure it are limited. We introduce a novel approach to probe media diet models -- language models adapted to online news, TV broadcast, or radio show content -- that can emulate the opinions of subpopulations that have consumed a set of media. To validate this method, we use as ground truth the opinions expressed in U.S. nationally representative surveys on COVID-19 and consumer confidence. Our studies indicate that this approach is (1) predictive of human judgements found in survey response distr…
Mapping Geopolitical Bias in 11 Large Language Models: A Bilingual, Dual-Framing Analysis of U.S.-China Tensions
Department of Industrial Engineering, Tsinghua University（清华大学工业工程系）；School of Social Sciences, Tsinghua University（清华大学社会科学部）；Department of Industrial Engineering, Federal University of Rio de Janeiro（里约热内卢联邦大学工业工程系）
Technical University of Darmstadt（达姆施塔特工业大学）；Johannes Gutenberg-University Mainz（美因茨约翰内斯·古腾堡大学）
This work investigates the use of interactively updated label suggestions to improve upon the efficiency of gathering annotations on the task of opinion mining in German Covid-19 social media data. We develop guidelines to conduct a controlled annotation study with social science students and find that suggestions from a model trained on a small, expert-annotated dataset already lead to a substantial improvement - in terms of inter-annotator agreement(+.14 Fleiss' $κ$) and annotation quality - compared to students that do not receive any label suggestions. We further find that label suggestion…
University of South Carolina（南卡罗来纳大学）；Auburn University at Montgomery（奥本大学蒙哥马利分校）
Opinion polls have been the bridge between public opinion and politicians in elections. However, developing surveys to disclose people's feedback with respect to economic issues is limited, expensive, and time-consuming. In recent years, social media such as Twitter has enabled people to share their opinions regarding elections. Social media has provided a platform for collecting a large amount of social media data. This paper proposes a computational public opinion mining approach to explore the discussion of economic issues in social media during an election. Current related studies use text…
University of Pennsylvania（宾夕法尼亚大学）；Beijing Normal University（北京师范大学）；National University of Singapore（新加坡国立大学）；University of Bern（伯尔尼大学）；Indian Institute of Technology, Jammu（印度理工学院查谟分校）
Modeling differential stress expressions in urban and rural regions in China can provide a better understanding of the effects of urbanization on psychological well-being in a country that has rapidly grown economically in the last two decades. This paper studies linguistic differences in the experiences and expressions of stress in urban-rural China from Weibo posts from over 65,000 users across 329 counties using hierarchical mixed-effects models. We analyzed phrases, topical themes, and psycho-linguistic word choices in Weibo posts mentioning stress to better understand appraisal difference…
Citing opinions is a powerful yet understudied strategy in argumentation. For example, an environmental activist might say, "Leading scientists agree that global warming is a serious concern," framing a clause which affirms their own stance ("that global warming is serious") as an opinion endorsed ("[scientists] agree") by a reputable source ("leading"). In contrast, a global warming denier might frame the same clause as the opinion of an untrustworthy source with a predicate connoting doubt: "Mistaken scientists claim [...]." Our work studies opinion-framing in the global warming (GW) debate,…
ADAPT Centre（ADAPT中心）；Dublin City University（都柏林城市大学）
Social media popularity and importance is on the increase due to people using it for various types of social interaction across multiple channels. This systematic review focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from user-generated content represented across multiple social media platforms and in various media formats, like text, image, video and audio. Through Social Opinion Mining, natural language can be understood in terms of the…
University of Exeter（埃克塞特大学）；Oxford Internet Institute（牛津互联网研究院）；University of Oxford（牛津大学）；King’s College London（伦敦国王学院）；Alan Turing Institute（艾伦·图灵研究所）；Meedan
Recent election surprises, regime changes, and political shocks indicate that political agendas have become more fast-moving and volatile. The ability to measure the complex dynamics of agenda change and capture the nature and extent of volatility in political systems is therefore more crucial than ever before. This study proposes a definition and operationalization of volatility that combines insights from political science, communications, information theory, and computational techniques. The proposed measures of fractionalization and agenda change encompass the shifting salience of issues i…
Cornell University（康奈尔大学）；Microsoft Research（微软研究院）；University of Bayreuth（拜罗伊特大学）；Tel Aviv University（特拉维夫大学）；Cornell Tech（康奈尔科技学院）
If large language models like GPT-3 preferably produce a particular point of view, they may influence people's opinions on an unknown scale. This study investigates whether a language-model-powered writing assistant that generates some opinions more often than others impacts what users write - and what they think. In an online experiment, we asked participants (N=1,506) to write a post discussing whether social media is good for society. Treatment group participants used a language-model-powered writing assistant configured to argue that social media is good or bad for society. Participants th…
People post their opinions and experiences on social media, yielding rich databases of end-users' sentiments. This paper shows to what extent machine learning can analyze and structure these databases. An automated data analysis pipeline is deployed to provide insights into user-generated content for researchers in other domains. First, the domain expert can select an image and a term of interest. Then, the pipeline uses image retrieval to find all images showing similar content and applies aspect-based sentiment analysis to outline users' opinions about the selected term. As part of an interd…
Network public opinion analysis is obtained by a combination of natural language processing (NLP) and public opinion supervision, and is crucial for monitoring public mood and trends. Therefore, network public opinion analysis can identify and solve potential and budding social problems. This study aims to realize an analysis of Chinese sentiment in social media reviews using a long short-term memory network (LSTM) model. The dataset was obtained from Sina Weibo using a web crawler and was cleaned with Pandas. First, Chinese comments regarding the legal sentencing in of Tangshan attack and Jia…
Samarkand State University（撒马尔罕国立大学）；University of Hertfordshire（赫特福德大学）；Lund University（隆德大学）
Opinion mining on social media posts has become more and more popular. Users often express their opinion on a topic not only with words but they also use image symbols such as emoticons and emoji. In this paper, we investigate the effect of emoji-based features in opinion classification of Uzbek texts, and more specifically movie review comments from YouTube. Several classification algorithms are tested, and feature ranking is performed to evaluate the discriminative ability of the emoji-based features.
World Health Organization (WHO) characterized the novel coronavirus (COVID-19) as a global pandemic on March 11th, 2020. Before this and in late January, more specifically on January 27th, while the majority of the infection cases were still reported in China and a few cruise ships, we began crawling social media user postings using the Twitter search API. Our goal was to leverage machine learning and linguistic tools to better understand the impact of the outbreak in China. Unlike our initial expectation to monitor a local outbreak, COVID-19 rapidly spread across the globe. In this short arti…
Earthquakes have a deep impact on wide areas, and emergency rescue operations may benefit from social media information about the scope and extent of the disaster. Therefore, this work presents a text miningbased approach to collect and analyze social media data for early earthquake impact analysis. First, disasterrelated microblogs are collected from the Sina microblog based on crawler technology. Then, after data cleaning a series of analyses are conducted including (1) the hot words analysis, (2) the trend of the number of microblogs, (3) the trend of public opinion sentiment, and (4) a key…
Institute of Experimental Design and Media Cultures (IXDM) FHNW（瑞士应用科学与艺术大学实验设计与媒体文化研究所（IXDM））
In social media, we communicate through pictures, videos, short codes, links, partial phrases. It is a rich, and digitally documented communication channel that relies on a multitude of media and forms. These channels are sorted by algorithms as organizers of discourse, mostly with the goal of channeling attention. In this research, we used Twitter to study the way Media Architecture is discussed within the community of architects, designers, researchers and policy makers. We look at the way they spontaneously share opinions on their engagement with digital infrastructures, networked places an…
