Volunteer-powered automatic classification of social media messages for public health in AIDR

2014 ◽  
Author(s):  
Muhammad Imran ◽  
Carlos Castillo
Keyword(s):  
Public Health ◽  
Social Media ◽  
Automatic Classification ◽  
Media Messages

scholarly journals Semantic Analysis of Open Source Data for Syndromic Surveillance

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Erica Briscoe ◽  
Scott Appling ◽  
Edward Clarkson ◽  
Nikolay Lipskiy ◽  
James Tyson ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Real Time ◽  
Topic Modeling ◽  
Syndromic Surveillance ◽  
Semantic Analysis ◽  
Human In The Loop ◽  
Media Messages ◽  
Recent Advances ◽  
Post Hoc

ObjectiveThe objective of this analysis is to leverage recent advances innatural language processing (NLP) to develop new methods andsystem capabilities for processing social media (Twitter messages)for situational awareness (SA), syndromic surveillance (SS), andevent-based surveillance (EBS). Specifically, we evaluated the useof human-in-the-loop semantic analysis to assist public health (PH)SA stakeholders in SS and EBS using massive amounts of publiclyavailable social media data.IntroductionSocial media messages are often short, informal, and ungrammatical.They frequently involve text, images, audio, or video, which makesthe identification of useful information difficult. This complexityreduces the efficacy of standard information extraction techniques1.However, recent advances in NLP, especially methods tailoredto social media2, have shown promise in improving real-time PHsurveillance and emergency response3. Surveillance data derived fromsemantic analysis combined with traditional surveillance processeshas potential to improve event detection and characterization. TheCDC Office of Public Health Preparedness and Response (OPHPR),Division of Emergency Operations (DEO) and the Georgia TechResearch Institute have collaborated on the advancement of PH SAthrough development of new approaches in using semantic analysisfor social media.MethodsTo understand how computational methods may benefit SS andEBS, we studied an iterative refinement process, in which the datauser actively cultivated text-based topics (“semantic culling”) in asemi-automated SS process. This ‘human-in-the-loop’ process wascritical for creating accurate and efficient extraction functions in large,dynamic volumes of data. The general process involved identifyinga set of expert-supplied keywords, which were used to collect aninitial set of social media messages. For purposes of this analysisresearchers applied topic modeling to categorize related messages intoclusters. Topic modeling uses statistical techniques to semanticallycluster and automatically determine salient aggregations. A user thensemantically culled messages according to their PH relevance.In June 2016, researchers collected 7,489 worldwide English-language Twitter messages (tweets) and compared three samplingmethods: a baseline random sample (C1, n=2700), a keyword-basedsample (C2, n=2689), and one gathered after semantically cullingC2 topics of irrelevant messages (C3, n=2100). Researchers utilizeda software tool, Luminoso Compass4, to sample and perform topicmodeling using its real-time modeling and Twitter integrationfeatures. For C2 and C3, researchers sampled tweets that theLuminoso service matched to both clinical and layman definitions ofRash, Gastro-Intestinal syndromes5, and Zika-like symptoms. Laymanterms were derived from clinical definitions from plain languagemedical thesauri. ANOVA statistics were calculated using SPSSsoftware, version. Post-hoc pairwise comparisons were completedusing ANOVA Turkey’s honest significant difference (HSD) test.ResultsAn ANOVA was conducted, finding the following mean relevancevalues: 3% (+/- 0.01%), 24% (+/- 6.6%) and 27% (+/- 9.4%)respectively for C1, C2, and C3. Post-hoc pairwise comparison testsshowed the percentages of discovered messages related to the eventtweets using C2 and C3 methods were significantly higher than forthe C1 method (random sampling) (p<0.05). This indicates that thehuman-in-the-loop approach provides benefits in filtering socialmedia data for SS and ESB; notably, this increase is on the basis ofa single iteration of semantic culling; subsequent iterations could beexpected to increase the benefits.ConclusionsThis work demonstrates the benefits of incorporating non-traditional data sources into SS and EBS. It was shown that an NLP-based extraction method in combination with human-in-the-loopsemantic analysis may enhance the potential value of social media(Twitter) for SS and EBS. It also supports the claim that advancedanalytical tools for processing non-traditional SA, SS, and EBSsources, including social media, have the potential to enhance diseasedetection, risk assessment, and decision support, by reducing the timeit takes to identify public health events.

scholarly journals Characterizing Social Media Messages Related to Underage JUUL E-Cigarette Buying and Selling: Cross-Sectional Analysis of Reddit Subreddits

10.2196/16962 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e16962
Author(s):  
Hejing Liu ◽  
Qiudan Li ◽  
Yongcheng Zhan ◽  
Zhu Zhang ◽  
Daniel D Zeng ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Keyword Search ◽  
Cross Sectional ◽  
Data Set ◽  
Media Messages ◽  
Social Media Platforms ◽  
Public Health Officials ◽  
Key Phrases ◽  
One Year

Background Stopping the epidemic of e-cigarette use among youth has become the common goal of both regulatory authorities and health departments. JUUL is currently the most popular e-cigarette brand on the market. Young people usually obtain and exchange information about JUUL with the help of social media platforms. Along with the rising prevalence of JUUL, posts about underage JUUL buying and selling have appeared on social media platforms such as Reddit, which sharply increase the risk of minors being exposed to JUUL. Objective This study aims to analyze Reddit messages about JUUL buying and selling among the users of the UnderageJuul subreddit, and to further summarize the characteristics of those messages. The findings and insights can contribute to a better understanding of the patterns of underage JUUL use, and help public health officials provide timely education and guidance to minors who have intentions of accessing JUUL. Methods We used a novel cross-subreddit method to analyze the Reddit messages on 2 subreddits. From July 9, 2017, to January 7, 2018, we collected data from the UnderageJuul subreddit, which was created for underage JUUL use discussion. The data set included 716 threads, 2935 comments, and 844 Reddit users (ie, Redditors). We collected our second data set, comprising 23,840 threads and 162,106 comments posted between July 9, 2017, and January 8, 2019, from the JUUL subreddit. We conducted analyses including the following: (1) annotation of users with buying/selling intention, (2) posting patterns discovery and topic comparison, and (3) posting activeness observation of discovered Redditors. Term frequency–inverse document frequency and regular expression-enhanced keyword search methods were applied during the content analysis to extract the posting patterns. The public posting records of the discovered users on the JUUL subreddit during the year after the UnderageJuul subreddit was shut down were analyzed to determine whether they were still active and interested in obtaining JUUL. Results Our study revealed the following: (1) Among the 716 threads on the UnderageJuul subreddit, there were 214 threads related to JUUL sale and 168 threads related to JUUL purchase, which accounted for 53.5% (382/714) of threads. (2) Among the 844 Redditors of the UnderageJuul subreddit, 23.82% (201/844) of users were annotated with buying intention, and 21.10% (178/844) of users were annotated with selling intention. There were 34 users with buying/selling intention that self-reported as being <21 years old. (3) The most common key phrases used in selling threads were “WTS,” “want to sell,” “for sale,” and “selling” (154/214, 72.0%). The most common key phrases used in buying threads were “look for/get JUUL/pods” (58/168, 34.5%) and “WTB” (53/168, 31.5%). (4) The most important concern that UnderageJuul Redditors had in obtaining JUULs was the price (311/1306, 23.81%), followed by the delivery service (68/1306, 5.21%). (5) The most popular flavors among the users with buying/selling intention were mango, cucumber, and mint. The flavor preferences remained consistent on both subreddits. Adverse symptoms related to the mango flavor were reported by 3 users on the JUUL subreddit. (6) In total, 24.4% (49/201) of users wanted to buy JUULs and 46.6% (83/178) of users wanted to sell JUULs, including 11 self-reported underage users, who also participated in the discussions on the JUUL subreddit. (7) Within one year of the UnderageJuul subreddit shutting down, there were 40 users who continued to post 186 threads on the JUUL subreddit, including 10 threads indicating buying/selling willingness that were posted shortly after the UnderageJuul subreddit was closed. Conclusions There were overlapping users active in the JUUL and UnderageJuul subreddits. The buying/selling-related content appeared in multiple venues with certain posting patterns from July 9, 2017, to January 7, 2018. Such content might lead to a high risk of health problems for minors, such as nicotine addiction. Based on these findings, this study provided some insights and suggestions that might contribute to the decision-making processes of regulators and public health officials.

A systematic mapping on automatic classification of fake news in social media

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
João Victor de Souza ◽  
Jorão Gomes ◽  
Fernando Marques de Souza Filho ◽  
Alessandreia Marta de Oliveira Julio ◽  
Jairo Francisco de Souza
Keyword(s):  
Social Media ◽  
Automatic Classification ◽  
Fake News ◽  
Systematic Mapping

scholarly journals Social Media Use, Disbelief and (Mis)information During a Pandemic: An Examination of Young Adult Nigerians’ Interactions with COVID-19 Public Health Messaging

2021 ◽  
pp. 1-18
Author(s):  
Olutobi Akingbade
Keyword(s):  
Public Health ◽  
Social Media ◽  
Young Adult ◽  
Low Income ◽  
Meaning Making ◽  
Health Messages ◽  
Media Messages ◽  
Public Health Messages ◽  
Social Media Platforms ◽  
The Government

This study contributes to transdisciplinary understanding of the COVID-19 pandemic through an examination of perceptions of public health messages as consumed primarily through social media by a purposively enlisted set of young adult Nigerians. The research used focus group discussions and in-depth interviews to elicit the views of 11 young adults, aged 21 to 24, resident in Ajegunle, a low-income community in Lagos, Nigeria’s commercial capital. The study identifies the centrality of social media platforms to the respondents’ processes of meaning-making, and draws on Hall’s (1980) encoding/decoding model in order to bring to the fore their oppositional interpretations of public health messages. The study also identifies respondents’ varying levels of disbelief about the realities of COVID-19, their mistrust of the government officials conveying and enforcing decisions to combat the pandemic, and the propensity for the social media messages they consume and propagate to serve as channels of misinformation.

A Systematic Review of Techniques Employed for Determining Mental Health Using Social Media in Psychological Surveillance During Disasters

2019 ◽  
Vol 14 (2) ◽  
pp. 265-272 ◽  
Author(s):  
Dhivya Karmegam ◽  
Thilagavathi Ramamoorthy ◽  
Bagavandas Mappillairajan
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Time Data ◽  
Social Media Data ◽  
Media Messages ◽  
The Social ◽  
Event Mining ◽  
Media Platform ◽  
Media Data

ABSTRACTDuring disasters, people share their thoughts and emotions on social media and also provide information about the event. Mining the social media messages and updates can be helpful in understanding the emotional state of people during such unforeseen events as they are real-time data. The objective of this review is to explore the feasibility of using social media data for mental health surveillance as well as the techniques used for determining mental health using social media data during disasters. PubMed, PsycINFO, and PsycARTICLES databases were searched from 2009 to November 2018 for primary research studies. After screening and analyzing the records, 18 studies were included in this review. Twitter was the widely researched social media platform for understanding the mental health of people during a disaster. Psychological surveillance was done by identifying the sentiments expressed by people or the emotions they displayed in their social media posts. Classification of sentiments and emotions were done using lexicon-based or machine learning methods. It is not possible to conclude that a particular technique is the best performing one, because the performance of any method depends upon factors such as the disaster size, the volume of data, disaster setting, and the disaster web environment.

scholarly journals Characterizing Social Media Messages Related to Underage JUUL E-Cigarette Buying and Selling: Cross-Sectional Analysis of Reddit Subreddits (Preprint)

2019 ◽  
Author(s):  
Hejing Liu ◽  
Qiudan Li ◽  
Yongcheng Zhan ◽  
Zhu Zhang ◽  
Daniel D Zeng ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Keyword Search ◽  
Cross Sectional ◽  
Data Set ◽  
Media Messages ◽  
Social Media Platforms ◽  
Public Health Officials ◽  
Key Phrases ◽  
One Year

BACKGROUND Stopping the epidemic of e-cigarette use among youth has become the common goal of both regulatory authorities and health departments. JUUL is currently the most popular e-cigarette brand on the market. Young people usually obtain and exchange information about JUUL with the help of social media platforms. Along with the rising prevalence of JUUL, posts about underage JUUL buying and selling have appeared on social media platforms such as Reddit, which sharply increase the risk of minors being exposed to JUUL. OBJECTIVE This study aims to analyze Reddit messages about JUUL buying and selling among the users of the UnderageJuul subreddit, and to further summarize the characteristics of those messages. The findings and insights can contribute to a better understanding of the patterns of underage JUUL use, and help public health officials provide timely education and guidance to minors who have intentions of accessing JUUL. METHODS We used a novel cross-subreddit method to analyze the Reddit messages on 2 subreddits. From July 9, 2017, to January 7, 2018, we collected data from the UnderageJuul subreddit, which was created for underage JUUL use discussion. The data set included 716 threads, 2935 comments, and 844 Reddit users (ie, Redditors). We collected our second data set, comprising 23,840 threads and 162,106 comments posted between July 9, 2017, and January 8, 2019, from the JUUL subreddit. We conducted analyses including the following: (1) annotation of users with buying/selling intention, (2) posting patterns discovery and topic comparison, and (3) posting activeness observation of discovered Redditors. Term frequency–inverse document frequency and regular expression-enhanced keyword search methods were applied during the content analysis to extract the posting patterns. The public posting records of the discovered users on the JUUL subreddit during the year after the UnderageJuul subreddit was shut down were analyzed to determine whether they were still active and interested in obtaining JUUL. RESULTS Our study revealed the following: (1) Among the 716 threads on the UnderageJuul subreddit, there were 214 threads related to JUUL sale and 168 threads related to JUUL purchase, which accounted for 53.5% (382/714) of threads. (2) Among the 844 Redditors of the UnderageJuul subreddit, 23.82% (201/844) of users were annotated with buying intention, and 21.10% (178/844) of users were annotated with selling intention. There were 34 users with buying/selling intention that self-reported as being &lt;21 years old. (3) The most common key phrases used in selling threads were “WTS,” “want to sell,” “for sale,” and “selling” (154/214, 72.0%). The most common key phrases used in buying threads were “look for/get JUUL/pods” (58/168, 34.5%) and “WTB” (53/168, 31.5%). (4) The most important concern that UnderageJuul Redditors had in obtaining JUULs was the price (311/1306, 23.81%), followed by the delivery service (68/1306, 5.21%). (5) The most popular flavors among the users with buying/selling intention were mango, cucumber, and mint. The flavor preferences remained consistent on both subreddits. Adverse symptoms related to the mango flavor were reported by 3 users on the JUUL subreddit. (6) In total, 24.4% (49/201) of users wanted to buy JUULs and 46.6% (83/178) of users wanted to sell JUULs, including 11 self-reported underage users, who also participated in the discussions on the JUUL subreddit. (7) Within one year of the UnderageJuul subreddit shutting down, there were 40 users who continued to post 186 threads on the JUUL subreddit, including 10 threads indicating buying/selling willingness that were posted shortly after the UnderageJuul subreddit was closed. CONCLUSIONS There were overlapping users active in the JUUL and UnderageJuul subreddits. The buying/selling-related content appeared in multiple venues with certain posting patterns from July 9, 2017, to January 7, 2018. Such content might lead to a high risk of health problems for minors, such as nicotine addiction. Based on these findings, this study provided some insights and suggestions that might contribute to the decision-making processes of regulators and public health officials.

Eating disorders during the COVID-19 pandemic: An overview of risks and recommendations for treatment and early intervention

2020 ◽  
Author(s):  
Marita Cooper ◽  
Erin E. Reilly ◽  
Jaclyn Amanda Siegel ◽  
Kathryn Coniglio ◽  
Shiri Sadeh-Sharvit ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Eating Disorders ◽  
Significant Risk ◽  
Coping Mechanisms ◽  
Treatment Access ◽  
Pertinent Literature ◽  
Health Crisis ◽  
Media Messages ◽  
Public Health Crisis

Individuals with eating disorders (EDs) are at significant risk for increases in symptomatology and diminished treatment access during the COVID-19 pandemic. Environmental precautions to limit coronavirus spread have affected food availability and access to healthy coping mechanisms, and have contributed to weight stigmatizing social media messages that may be uniquely harmful for those experiencing EDs. Additionally, changes in socialization and routine, stress, and experiences of trauma that are being experienced globally may be particularly deleterious to ED risk and recovery. This paper presents a brief review of the pertinent literature related to risk of EDs in the context of COVID-19 and offers suggestions for modifying intervention efforts to accommodate for the unique challenges individuals with EDs and providers may be experiencing in light of the ongoing public health crisis.

scholarly journals Effect of dramatized health messages: Modelling predictors of the impact of COVID-19 YouTube animated cartoons on health behaviour of social media users in Nigeria

2020 ◽  
Vol 36 (1) ◽  
pp. 124-140
Author(s):  
Chijioke Onuora ◽  
Nelson Torti Obasi ◽  
Gregory Herbert Ezeah ◽  
Verlumun Celestine Gever
Keyword(s):  
Public Health ◽  
Social Media ◽  
Health Promotion ◽  
Developing Country ◽  
Health Behaviour ◽  
Health Messages ◽  
Public Health Issue ◽  
Media Messages ◽  
The Impact ◽  
The Relationship

Previous studies on the impact of Internet-powered media on health promotion have often neglected the relationship between message recall and health behaviour. Such neglect makes it look as though exposure to media messages automatically leads to recall. Also, other studies appear to have paid less attention to understanding if the perception of the existence or otherwise of a public health issue actually influences the effectiveness of health intervention. In the current study, the authors suggest a model that takes into consideration these existing gaps. They examined 470 social media users who were exposed to YouTube animated cartoons on COVID-19 using an example from a developing country. The authors found, among others, that perception concerning the realness of COVID-19 was the greatest contributing factor in predicting the effectiveness of YouTube animated cartoons on health behaviour. The scholarly theoretical and practical contributions of the findings are explored.

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