scholarly journals What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques

2015 ◽  
Vol 17 (9) ◽  
pp. e220 ◽  
Author(s):  
Annie T Chen ◽  
Shu-Hong Zhu ◽  
Mike Conway
Keyword(s):  
Text Mining ◽  
Online Communities ◽  
Electronic Cigarettes ◽  
Visualization Techniques

scholarly journals Combining Text Mining and Data Visualization Techniques to Understand Consumer Experiences of Electronic Cigarettes and Hookah in Online Forums

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Annie T. Chen ◽  
Shu-Hong Zhu ◽  
Mike Conway
Keyword(s):  
Text Mining ◽  
Data Visualization ◽  
Electronic Cigarettes ◽  
Discussion Forums ◽  
Online Forums ◽  
Textual Data ◽  
Consumer Experiences ◽  
Visualization Techniques

Our aim in this work is to apply text mining and novel visualization techniques to textual data derived from online health discussion forums in order to better understand consumers experiences and perceptions of electronic cigarettes and hookah.

scholarly journals In Search of New Product Ideas: Identifying Ideas in Online Communities by Machine Learning and Text Mining

2016 ◽  
Vol 26 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Kasper Christensen ◽  
Sladjana Nørskov ◽  
Lars Frederiksen ◽  
Joachim Scholderer
Keyword(s):  
Machine Learning ◽  
Text Mining ◽  
Online Communities ◽  
New Product

scholarly journals The Twitter Narrative: An Essential Perspective for Comparative Analyses on Emerging Tobacco Products (Preprint)

2015 ◽  
Author(s):  
Joyce Danielle Sharpe
Keyword(s):  
Content Analysis ◽  
Tobacco Use ◽  
Online Communities ◽  
Online Community ◽  
Underserved Populations ◽  
Electronic Cigarettes ◽  
Online Forums ◽  
Significant Information ◽  
Tobacco Products ◽  
Comparative Analyses

BACKGROUND In a recently published article, Chen and colleagues compared online discussions about electronic cigarettes and hookah use amongst different Internet communities [1]. With great interest, I found the Chen et al. article to provide insightful and novel findings in regards to understanding the variances in tobacco use behaviors amongst the online forums included in the study. OBJECTIVE In their limitations, Chen et al. recognized that the use of three websites –Vapor Talk, Hookah Forum, and Reddit – was not extensive nor inclusive of the various online communities that exist for tobacco products. The authors’ rationale for selecting the three websites was to assess similarities and differences between different types of online communities. However, it would have provided an interesting perspective to include Twitter discussions about hookah and electronic cigarette use because Twitter is a diverse online community in itself. METHODS Young adults, urban residents, Hispanics, and African Americans are overrepresented populations on Twitter in comparison to the general population [2]. These groups of people are typically overrepresented in vulnerable populations, as well. Therefore, including Twitter data in this comparative study could have captured significant information on tobacco use behaviors of hard-to-reach and underserved populations. RESULTS To my knowledge, there has been no previous research that has comparatively analyzed online communities for experiences with emerging tobacco products, such as electronic cigarettes and hookah. Although several studies have conducted content analyses of Twitter discussions about hookah and electronic cigarettes [3-5], there are no studies comparing Twitter to other online communities. Future work should include Twitter in such comparative analyses in order to provide further outlooks on how tobacco use behaviors of Twitter subscribers are identical and different from users of other online forums, which can then inform and tailor health education interventions based on the particular online community. CONCLUSIONS References 1. Chen, AT, Zhu, SH, Conway, M. What online communities can tell us about electronic cigarettes and hookah use: A study using text mining and visualization techniques. J Med Internet Res 2015;17(9):e220. PMID:26420469. 2. Mislove, A, Lehmann, S, Ahn, Y, Onnela, J, Rosenquist, JN. Understanding the demographics of Twitter users. Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media; 2011 July 17-21; Barcelona, Spain. 2011. 3. Myslín M, Zhu S, Chapman W, Conway M. Using Twitter to examine smoking behavior and perceptions of emerging tobacco products. J Med Internet Res 2013;15(8):e174. doi:10.2196/jmir.2534. 4. Krauss, MJ, et al. (2015). Hookah-related Twitter chatter: A content analysis. Prev Chronic Dis 2015;12:e121. PMID:26226068. 5. Cole-Lewis, H, et al. (2015). Social listening: A content analysis of e-cigarette discussions on Twitter. J Med Internet Res 2015;17(10):e243. PMID:26508089.

What the Public say about E-cigarettes on Chinese Social Media: Combining Text-mining Analysis and Correspondence Analysis (Preprint)

2020 ◽  
Author(s):  
Joanne Chen Lyu
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Correspondence Analysis ◽  
Electronic Cigarettes ◽  
Public Discussion ◽  
The Public ◽  
Public Health Professionals ◽  
Period 2 ◽  
Access Information ◽  
Chinese Public

BACKGROUND Electronic cigarettes have become increasingly popular. China has accelerated its legislation on e-cigarettes in recent years by issuing two policies to regulate their use; firstly, on August 26, 2018 and secondly, on November 1, 2019. Social media provides an efficient platform to access information on the public opinion of e-cigarettes. OBJECTIVE In order to get an insight into how policies have influenced the reaction of the Chinese public to e-cigarettes, this study seeks to understand what the Chinese public say about e-cigarettes, and how the focus of discussion might have changed in the context of policy implementation. METHODS This study used a combination of text mining and correspondence analysis. From January 1, 2017 to December 31, 2019, Python was used to text mine the most frequently used words/phrases in public e-cigarette discussion on Zhihu, China’s largest question-and-answer platform and one of the country’s most trustworthy social media sources. Correspondence analysis was used to examine the similarities and differences between high-frequency words across three time periods (i.e., 2017/1/1-2018/8/27, 2018/8/28-2019/10/31, 2019/11/1-2020/1/1). RESULTS Results showed that the consistent themes across time were comparisons with traditional cigarettes; health concerns; and how to choose e-cigarette products. The issuance of government policies on e-cigarettes led to a change in the focus of public discussion. The discussion of e-cigarettes in period 1 mainly focused on the use and experience of e-cigarettes. In period 2, the public’s attention was not only on the substances related to e-cigarettes, but also on the smoking cessation functions of e-cigarettes. In period 3, the public shifted their attention to the e-cigarette industry and government policy on the banning of sales of e-cigarettes to minors. CONCLUSIONS Social media is an informative source which can help policymakers and public health professionals understand the public's concerns over and understanding of e-cigarettes. When there was little regulation, public discussion was greatly influenced by industry claims about e-cigarettes; however, once e-cigarette policies were issued, these policies, to a large extent, set the agenda for public discussion. In addition, media reporting of these policies might have greatly influenced the way e-cigarette policies were discussed. Therefore, monitoring e-cigarette discussion on social media and responding to it in a timely manner will both help improve the public's e-cigarette literacy and facilitate the implementation of e-cigarette related policies. CLINICALTRIAL Not Applicable.

scholarly journals Text Mining for Social Research: A Reddit-based Case Study of George Floyd

2020 ◽  
Author(s):  
Marina Wiebe
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Online Communities ◽  
Social Research ◽  
Public Forum ◽  
The World

Social media sources such as Reddit allow for a large public forum to share opinions and ideas. The discussions in these online communities often reflect events occurring around the world. These discussions can also be influenced and shaped by the participation of political figures online. Using Reddit's public API, comments were scraped in prominent policing related Subreddits during the week of George Floyd's death to understand how his death and Donald's Trump's response to the subsequent rioting influenced the tone of discussion.

Exploring the Context of Pioneer Missionary in Northern Taiwan by Analyzing George Leslie Mackay's Diary

2013 ◽  
Vol 411-414 ◽  
pp. 86-89
Author(s):  
Leuo Hong Wang
Keyword(s):  
Content Analysis ◽  
Text Mining ◽  
Data Visualization ◽  
Computational Techniques ◽  
Missionary Work ◽  
Analysis Methodology ◽  
Visualization Techniques ◽  
Northern Taiwan

George Leslie Mackay (1844-1901), the first Presbyterian missionary to northern Taiwan, is considered to be one of the most important persons who influence the development of education and medicine in Taiwan. Recently, the manuscripts written by Mackay which detailed his work from 1871 to 1901 in Taiwan have been computerized and published as Mackays diaries. Researchers who are interested in historical topics concerning religious, educational and medical development in Taiwan hence concentrate their attention on these materials. However, little research applied computational techniques to analyze the content of the diaries. That motivated us to apply text mining techniques to explore the content of diaries. The content analysis methodology was used in this research to unveil the context of Mackays missionary work in northern Taiwan. Finally, the context was presented by data visualization techniques.

scholarly journals Public Opinion About E-Cigarettes on Chinese Social Media: A Combined Study of Text Mining Analysis and Correspondence Analysis

10.2196/19804 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e19804
Author(s):  
Di Wang ◽  
Joanne Chen Lyu ◽  
Xiaoyu Zhao
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Text Mining ◽  
Correspondence Analysis ◽  
Electronic Cigarettes ◽  
Public Discussion ◽  
The Public ◽  
Public Health Professionals ◽  
Period 2 ◽  
Chinese Public

Background Electronic cigarettes (e-cigarettes) have become increasingly popular. China has accelerated its legislation on e-cigarettes in recent years by issuing two policies to regulate their use: the first on August 26, 2018, and the second on November 1, 2019. Social media provide an efficient platform to access information on the public opinion of e-cigarettes. Objective To gain insight into how policies have influenced the reaction of the Chinese public to e-cigarettes, this study aims to understand what the Chinese public say about e-cigarettes and how the focus of discussion might have changed in the context of policy implementation. Methods This study uses a combination of text mining and correspondence analysis to content analyze 1160 e-cigarette–related questions and their corresponding answers from Zhihu, China’s largest question-and-answer platform and one of the country’s most trustworthy social media sources. From January 1, 2017, to December 31, 2019, Python was used to text mine the most frequently used words and phrases in public e-cigarette discussions on Zhihu. The correspondence analysis was used to examine the similarities and differences between high-frequency words and phrases across 3 periods (ie, January 1, 2017, to August 27, 2018; August 28, 2018, to October 31, 2019; and November 1, 2019, to January 1, 2020). Results The results of the study showed that the consistent themes across time were comparisons with traditional cigarettes, health concerns, and how to choose e-cigarette products. The issuance of government policies on e-cigarettes led to a change in the focus of public discussion. The discussion of e-cigarettes in period 1 mainly focused on the use and experience of e-cigarettes. In period 2, the public’s attention was not only on the substances related to e-cigarettes but also on the smoking cessation functions of e-cigarettes. In period 3, the public shifted their attention to the e-cigarette industry and government policy on the banning of e-cigarette sales to minors. Conclusions Social media are an informative source, which can help policy makers and public health professionals understand the public’s concerns over and understanding of e-cigarettes. When there was little regulation, public discussion was greatly influenced by industry claims about e-cigarettes; however, once e-cigarette policies were issued, these policies, to a large extent, set the agenda for public discussion. In addition, media reporting of these policies might have greatly influenced the way e-cigarette policies were discussed. Therefore, monitoring e-cigarette discussions on social media and responding to them in a timely manner will both help improve the public’s e-cigarette literacy and facilitate the implementation of e-cigarette–related policies.

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