19 research outputs found
American Twitter Users Revealed Social Determinants-related Oral Health Disparities amid the COVID-19 Pandemic
Objectives: To assess self-reported population oral health conditions amid
COVID-19 pandemic using user reports on Twitter. Method and Material: We
collected oral health-related tweets during the COVID-19 pandemic from 9,104
Twitter users across 26 states (with sufficient samples) in the United States
between November 12, 2020 and June 14, 2021. We inferred user demographics by
leveraging the visual information from the user profile images. Other
characteristics including income, population density, poverty rate, health
insurance coverage rate, community water fluoridation rate, and relative change
in the number of daily confirmed COVID-19 cases were acquired or inferred based
on retrieved information from user profiles. We performed logistic regression
to examine whether discussions vary across user characteristics. Results:
Overall, 26.70% of the Twitter users discuss wisdom tooth pain/jaw hurt, 23.86%
tweet about dental service/cavity, 18.97% discuss chipped tooth/tooth break,
16.23% talk about dental pain, and the rest are about tooth decay/gum bleeding.
Women and younger adults (19-29) are more likely to talk about oral health
problems. Health insurance coverage rate is the most significant predictor in
logistic regression for topic prediction. Conclusion: Tweets inform social
disparities in oral health during the pandemic. For instance, people from
counties at a higher risk of COVID-19 talk more about tooth decay/gum bleeding
and chipped tooth/tooth break. Older adults, who are vulnerable to COVID-19,
are more likely to discuss dental pain. Topics of interest vary across user
characteristics. Through the lens of social media, our findings may provide
insights for oral health practitioners and policy makers.Comment: Accepted for publication in Quintessence Internationa
Look behind the Censorship: Reposting-User Characterization and Muted-Topic Restoration
The emergence of social media has largely eased the way people receive
information and participate in public discussions. However, in countries with
strict regulations on discussions in the public space, social media is no
exception. To limit the degree of dissent or inhibit the spread of "harmful"
information, a common approach is to impose information operations such as
censorship/suspension on social media. In this paper, we focus on a study of
censorship on Weibo, the counterpart of Twitter in China. Specifically, we 1)
create a web-scraping pipeline and collect a large dataset solely focus on the
reposts from Weibo; 2) discover the characteristics of users whose reposts
contain censored information, in terms of gender, device, and account type; and
3) conduct a thematic analysis by extracting and analyzing topic information.
Note that although the original posts are no longer visible, we can use
comments users wrote when reposting the original post to infer the topic of the
original content. We find that such efforts can recover the discussions around
social events that triggered massive discussions but were later muted. Further,
we show the variations of inferred topics across different user groups and time
frames.Comment: Accepted for publication in Proceedings of the International Workshop
on Social Sensing (SocialSens 2022): Special Edition on Belief Dynamics, 202
Bias or Diversity? Unraveling Semantic Discrepancy in U.S. News Headlines
There is a broad consensus that news media outlets incorporate ideological
biases in their news articles. However, prior studies on measuring the
discrepancies among media outlets and further dissecting the origins of
semantic differences suffer from small sample sizes and limited scope. In this
study, we collect a large dataset of 1.8 million news headlines from major U.S.
media outlets spanning from 2014 to 2022 to thoroughly track and dissect the
semantic discrepancy in U.S. news media. We employ multiple correspondence
analysis (MCA) to quantify the semantic discrepancy relating to four prominent
topics - domestic politics, economic issues, social issues, and foreign
affairs. Additionally, we compare the most frequent n-grams in media headlines
to provide further qualitative insights into our analysis. Our findings
indicate that on domestic politics and social issues, the discrepancy can be
attributed to a certain degree of media bias. Meanwhile, the discrepancy in
reporting foreign affairs is largely attributed to the diversity in individual
journalistic styles. Finally, U.S. media outlets show consistency and high
similarity in their coverage of economic issues