scholarly journals Public Opinions towards COVID-19 in California and New York on Twitter

2020 ◽  
Author(s):  
Xueting Wang ◽  
Canruo Zou ◽  
Zidian Xie ◽  
Dongmei Li
Keyword(s):  
New York ◽  
Social Media ◽  
Topic Modeling ◽  
New York State ◽  
The United States ◽  
Public Opinions ◽  
Online Social Media ◽  
Twitter Users ◽  
Negative Sentiment ◽  
Over Time

Background: With the pandemic of COVID-19 and the release of related policies, discussions about the COVID-19 are widespread online. Social media becomes a reliable source for understanding public opinions toward this virus outbreak. Objective: This study aims to explore public opinions toward COVID-19 on social media by comparing the differences in sentiment changes and discussed topics between California and New York in the United States. Methods: A dataset with COVID-19-related Twitter posts was collected from March 5, 2020 to April 2, 2020 using Twitter streaming API. After removing any posts unrelated to COVID-19, as well as posts that contain promotion and commercial information, two individual datasets were created based on the geolocation tags with tweets, one containing tweets from California state and the other from New York state. Sentiment analysis was conducted to obtain the sentiment score for each COVID-19 tweet. Topic modeling was applied to identify top topics related to COVID-19. Results: While the number of COVID-19 cases increased more rapidly in New York than in California in March 2020, the number of tweets posted has a similar trend over time in both states. COVID-19 tweets from California had more negative sentiment scores than New York. There were some fluctuations in sentiment scores in both states over time, which might correlate with the policy changes and the severity of COVID-19 pandemic. The topic modeling results showed that the popular topics in both California and New York states are similar, with "protective measures" as the most prevalent topic associated with COVID-19 in both states. Conclusions: Twitter users from California had more negative sentiment scores towards COVID-19 than Twitter users from New York. The prevalent topics about COVID-19 discussed in both states were similar with some slight differences.

Public Reactions to the New York State Policy on Flavored E-Cigarettes on Twitter: Observational Study (Preprint)

2020 ◽  
Author(s):  
Li Sun ◽  
Xinyi Lu ◽  
Zidian Xie ◽  
Dongmei Li
Keyword(s):  
New York ◽  
Sentiment Analysis ◽  
State Policy ◽  
Topic Modeling ◽  
Electronic Cigarettes ◽  
Public Attitudes ◽  
New York State ◽  
York State ◽  
Before And After ◽  
Twitter Users

BACKGROUND Flavored electronic cigarettes (e-cigarettes) have become popular in recent years, especially among youth and young adults. To address the epidemic of e-cigarettes, New York State approved a ban on sales of most flavored vaping products other than tobacco and menthol flavors on September 17, 2019. OBJECTIVE This study aimed to examine the public responses on social media to the policy on flavored e-cigarettes in New York State. METHODS Twitter posts (tweets) related to e-cigarettes and the New York State policy on flavored e-cigarettes were collected using Twitter streaming API from June 2019 to December 2019. Tweets from New York State, and other states that did not have a flavored e-cigarettes policy were extracted. Sentiment analysis was applied to analyze the proportion of negative and positive tweets about e-cigarettes or the flavor policy. Topic modeling was applied to e-cigarettes related datasets to identify the most frequent topics before and after the announcement of the New York State policy on flavored e-cigarettes. RESULTS Our results showed that average number of tweets related to e-cigarettes and the New York State policy on flavored e-cigarettes increased in both New York State and other states after the NY flavor policy was announced. Sentiment analysis revealed that after the announcement of the New York State flavor policy, in both New York State and other states, the proportion of negative tweets on e-cigarettes increased, from 34.07% to 44.58% and from 32.48% to 44.40% respectively, while positive tweets decreased significantly, from 39.03% to 32.86% and from 42.78% to 33.93% respectively. The majority of tweets about the New York State flavor policy were negative in both New York State (from 88.78% to 83.46%) and other states (from 78.43% to 81.54%) while New York State had a higher proportion of negative tweets than other states. Topic modeling results demonstrated that teenage vaping and health problems were the most discussed topic associated with e-cigarettes. CONCLUSIONS Public attitudes toward e-cigarettes became more negative on Twitter after the New York State announced the policy on flavored e-cigarettes. Twitter users in other states that did not have such a policy on flavored e-cigarettes paid close attention to New York State flavor policy. This study provides some valuable information about the potential impact of the flavored e-cigarettes policy in New York State on public attitudes towards the flavored e-cigarettes.

Social Media Activism and Convergence in Tweet Topics After the Initial #MeToo Movement for Two Distinct Groups of Twitter Users

2021 ◽  
pp. 088626052110014
Author(s):  
Jason M. Baik ◽  
Thet H. Nyein ◽  
Sepideh Modrek
Keyword(s):  
Social Media ◽  
Sexual Assault ◽  
Frequency Analysis ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Bigram Frequency ◽  
Media Activism ◽  
Online Social Media ◽  
Before And After ◽  
Twitter Users

Online social media movements are now common and support cultural discussions on difficult health and social topics. The #MeToo movement, focusing on the pervasiveness of sexual assault and harassment, has been one of the largest and most influential online movements. Our study examines topics of conversation on Twitter by supporters of the #MeToo movement and by Twitter users who were uninvolved in the movement to explore the extent to which tweet topics for these two groups converge over time. We identify and collect one year’s worth of tweets for supporters of the #MeToo movement ( N = 168 users; N = 105,538 tweets) and users not involved in the movement ( N = 147 users; N = 112,301 tweets referred to as the Neutral Sample). We conduct topic frequency analysis and implement an unsupervised machine learning topic modeling algorithm, latent Dirichlet allocation, to explore topics of discussion on Twitter for these two groups of users before and after the initial #MeToo movement. Our results suggest that supporters of #MeToo discussed different topics compared to the Neutral Sample of Twitter users before #MeToo with some overlap on politics. The supporters were already discussing sexual assault and harassment issues six months before #MeToo, and discussion on this topic increased 13.7-fold in the six months after. For the Neutral Sample, sexual assault and harassment was not a key topic of discussion on Twitter before #MeToo, but there was some limited increase afterward. Results of bigram frequency analysis and topic modeling showed a clear increase in topic related to gender for the supporters of #MeToo but gave mixed results for the Neutral Sample comparison group. Our results suggest limited shifts in the conversation on Twitter for the Neutral Sample. Our methods and results have implications for measuring the extent to which online social media movements, like #MeToo, reach a broad audience.

A Perspective of Electronic Cigarette Users on the COVID-19 Pandemic in Twitter: Observational Study (Preprint)

2020 ◽  
Author(s):  
Yankun Gao ◽  
Zidian Xie ◽  
Dongmei Li
Keyword(s):  
Social Media ◽  
Immune Responses ◽  
Sentiment Analysis ◽  
Topic Modeling ◽  
Electronic Cigarette ◽  
Virus Infections ◽  
Twitter Data ◽  
The Us ◽  
Twitter Users ◽  
Negative Sentiment

BACKGROUND Previous studies indicated electronic cigarette users might be more vulnerable to COVID-19 infections and could develop more severe symptoms once contracted COVID-19 due to their impaired immune responses to virus infections. Social media has been widely used to express users’ responses to the COVID-19 pandemic. OBJECTIVE We aimed to examine the responses of electronic cigarette Twitter users to the COVID-19 pandemic using Twitter data. METHODS The COVID-19 dataset contained COVID-19-related Twitter posts (tweets) between March 5th, 2020 and April 3rd, 2020. Ecig group included Twitter users who didn’t have commercial accounts but ever retweeted e-cigarette promotion posts between May 2019 and August 2019. Twitter users who didn’t post or retweet any e-cigarette-related tweets were defined as Non-Ecig group. Sentiment analysis was conducted to compare sentiment scores towards the COVID-19 pandemic between both groups. Topic modeling was used to compare the main topics discussed between the two groups. RESULTS The US COVID-19 dataset consisted of 1,112,558 COVID-19-related tweets from 15,657 unique Twitter users in the Ecig group and 9,789,584 COVID-19-related tweets from 2,128,942 unique Twitter users in the Non-Ecig group. Sentiment analysis showed that the Ecig group have more negative sentiment scores than the Non-Ecig group. Results from topic modeling indicated the Ecig group had more concern about COVID-19 related death, while the Non-Ecig group cared more about the government’s responses to the COVID-19 pandemic. CONCLUSIONS Electronic cigarette Twitter users has more concern towards the COVID-19 pandemic. Twitter is a useful tool to timely monitor public responses to the COVID-19 pandemic.

scholarly journals Social Media Study of Public Opinions on Potential COVID-19 Vaccines: Informing Dissent, Disparities, and Dissemination

2020 ◽  
Author(s):  
Hanjia Lyu ◽  
Junda Wang ◽  
Wei Wu ◽  
Viet Duong ◽  
Xiyang Zhang ◽  
...  
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Multinomial Logistic Regression ◽  
The United States ◽  
Effective Vaccine ◽  
Political Issues ◽  
Public Opinions ◽  
Media Study ◽  
The People ◽  
Twitter Users

AbstractThe current development of vaccines for SARS-CoV-2 is unprecedented. Little is known, however, about the nuanced public opinions on the coming vaccines. We adopt a human-guided machine learning framework (using more than 40,000 rigorously selected tweets from more than 20,000 distinct Twitter users) to capture public opinions on the potential vaccines for SARS-CoV-2, classifying them into three groups: pro-vaccine, vaccine-hesitant, and anti-vaccine. We aggregate opinions at the state and country levels, and find that the major changes in the percentages of different opinion groups roughly correspond to the major pandemic-related events. Interestingly, the percentage of the pro-vaccine group is lower in the Southeast part of the United States. Using multinomial logistic regression, we compare demographics, social capital, income, religious status, political affiliations, geo-locations, sentiment of personal pandemic experience and non-pandemic experience, and county-level pandemic severity perception of these three groups to investigate the scope and causes of public opinions on vaccines. We find that socioeconomically disadvantaged groups are more likely to hold polarized opinions on potential COVID-19 vaccines. The anti-vaccine opinion is the strongest among the people who have the worst personal pandemic experience. Next, by conducting counterfactual analyses, we find that the U.S. public is most concerned about the safety, effectiveness, and political issues regarding potential vaccines for COVID-19, and improving personal pandemic experience increases the vaccine acceptance level. We believe this is the first large-scale social media-based study to analyze public opinions on potential COVID-19 vaccines that can inform more effective vaccine distribution policies and strategies.

Seasonal Activity of Haemaphysalis longicornis (Acari: Ixodidae) in Southern New York State

2020 ◽  
Author(s):  
Nicholas P Piedmonte ◽  
Vanessa C Vinci ◽  
Thomas J Daniels ◽  
Bryon P Backenson ◽  
Richard C Falco
Keyword(s):  
United States ◽  
New York ◽  
Activity Patterns ◽  
New York State ◽  
The United States ◽  
Haemaphysalis Longicornis ◽  
Seasonal Activity ◽  
Eastern Asia ◽  
Short Life ◽  
Human Bite

Abstract The Asian longhorned tick, Haemaphysalis longicornis Neumann, is a species native to eastern Asia that has recently been discovered in the United States. In its native range, H. longicornis transmits pathogens that cause disease in humans and livestock. It is currently unknown whether H. longicornis will act as a vector in the United States. Understanding its seasonal activity patterns will be important in identifying which times of the year represent greatest potential risk to humans and livestock should this species become a threat to animal or public health. A study site was established in Yonkers, NY near the residence associated with the first reported human bite from H. longicornis in the United States. Ticks were collected once each week from July 2018 to November 2019. Haemaphysalis longicornis larvae were most active from August to November, nymphs from April to July, and adult females from June to September. This pattern of activity suggests that H. longicornis is capable of completing a generation within a single year and matches the patterns observed in its other ranges in the northern hemisphere. The data presented here contribute to a growing database for H. longicornis phenology in the northeastern United States. Potential implications of the short life cycle for the tick’s vectorial capacity are discussed.

Geographic Variation in Dominance of Spinosad Resistance in Colorado Potato Beetles (Coleoptera: Chrysomelidae)

2020 ◽  
Author(s):  
Coby Klein ◽  
Mitchell Baker ◽  
Andrei Alyokhin ◽  
David Mota-Sanchez
Keyword(s):  
New York ◽  
Long Island ◽  
New York State ◽  
The United States ◽  
Island Population ◽  
Potato Beetle ◽  
Rate Of Increase ◽  
Short Period ◽  
Leptinotarsa Decemlineata Say ◽  
High Level

Abstract Eastern New York State is frequently the site of Colorado potato beetle (Leptinotarsa decemlineata, Say) populations with the highest observed levels of insecticide resistance to a range of active ingredients. The dominance of a resistant phenotype will affect its rate of increase and the potential for management. On organic farms on Long Island, L. decemlineata evolved high levels of resistance to spinosad in a short period of time and that resistance has spread across the eastern part of the Island. Resistance has also emerged in other parts of the country as well. To clarify the level of dominance or recessiveness of spinosad resistance in different parts of the United States and how resistance differs in separate beetle populations, we sampled in 2010 beetle populations from Maine, Michigan, and Long Island. In addition, a highly resistant Long Island population was assessed in 2012. All populations were hybridized with a laboratory-susceptible strain to determine dominance. None of the populations sampled in 2010 were significantly different from additive resistance, but the Long Island population sampled in 2012 was not significantly different from fully recessive. Recessive inheritance of high-level resistance may help manage its increase.

Management of personal protective equipment during the COVID-19 pandemic in England and the state of New York: A comparative case study

2020 ◽  
Vol 18 (7) ◽  
pp. 71-89
Author(s):  
Amy Barber, BSc ◽  
Annaëlle Vinzent, BS ◽  
Imani Williams, BA
Keyword(s):  
New York ◽  
Supply Chain ◽  
Health Systems ◽  
Personal Protective Equipment ◽  
New York State ◽  
The United States ◽  
Mitigation Strategies ◽  
Comparative Case Study ◽  
Protective Equipment

Background: The COVID-19 crisis placed extraordinary demands on the supply of personal protective equipment (PPE) at the beginning of 2020. These were coupled with shocks to the supply chain resulting from the disease. Many typically well-resourced health systems faced subsequent shortages of equipment and had to implement new strategies to manage their stocks. Stockpiles of protective equipment were held in both the United States and United Kingdom intended to prevent shortages. Method: Cross-comparative case study approach by applying Pettigrew and Whipp’s framework for change management. Setting: The health systems of England and New York state from January 2020 to the end of April 2020. Results: Both cases reacted slowly to their outbreaks and faced problems with supplying enough PPE to their health systems. Their stockpiles were not enough to prevent shortages, with many distribution problems resulting from inadequate governance mechanisms. No sustainable responses to supply disruptions were implemented during the study period in either case. Health systems planned interventions along each part of the supply chain from production and importing, to usage guidelines. Conclusion: Global supply chains are vulnerable to disruptions caused by international crises, and existing mitigation strategies have not been wholly successful. The existence of stockpiles is insufficient to preventing shortages of necessary equipment in clinical settings. Both the governance and quality of stockpiles, as well as distribution channels are important for preventing shortages. At the time of writing, it is not possible to judge the strength of strategies adopted in these cases.

scholarly journals Three months of informational trends in COVID-19 across New York City

2020 ◽  
Vol 42 (3) ◽  
pp. 448-450
Author(s):  
Wil Lieberman-Cribbin ◽  
Naomi Alpert ◽  
Adam Gonzalez ◽  
Rebecca M Schwartz ◽  
Emanuela Taioli
Keyword(s):  
New York ◽  
New York City ◽  
York City ◽  
Information Seeking ◽  
New York State ◽  
Search Term ◽  
Multiple Sources ◽  
The Usa ◽  
Trend Data ◽  
Over Time

Abstract In the midst of widespread community transmission of coronavirus disease 2019 (COVID-19) in New York, residents have sought information about COVID-19. We analyzed trends in New York State (NYS) and New York City (NYC) data to quantify the extent of COVID-19-related queries. Data on the number of 311 calls in NYC, Google Trend data on the search term ‘Coronavirus’ and information about trends in COVID-19 cases in NYS and the USA were compiled from multiple sources. There were 1228 994 total calls to 311 between 22 January 2020 and 22 April 2020, with 50 845 calls specific to COVID-19 in the study period. The proportion of 311 calls related to COVID-19 increased over time, while the ‘interest over time’ of the search term ‘Coronavirus’ has exponentially increased since the end of February 2020. It is vital that public health officials provide clear and up-to-date information about protective measures and crucial communications to respond to information-seeking behavior across NYC.

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