scholarly journals Social Media Content About Children’s Pain and Sleep: Content and Network Analysis (Preprint)

2018 ◽  
Author(s):  
Michelle E Tougas ◽  
Christine T Chambers ◽  
Penny Corkum ◽  
Julie M Robillard ◽  
Anatoliy Gruzd ◽  
...  
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Child Health ◽  
Information Exchange ◽  
Research Evidence ◽  
Specific Information ◽  
User Engagement ◽  
User Interactions ◽  
Personal Experiences ◽  
Children's Pain

BACKGROUND Social media is often used for health communication and can facilitate fast information exchange. Despite its increasing use, little is known about child health information sharing and engagement over social media. OBJECTIVE The primary objectives of this study are to systematically describe the content of social media posts about child pain and sleep and identify the level of research evidence in these posts. The secondary objective is to examine user engagement with information shared over social media. METHODS Twitter, Instagram, and Facebook were searched by members of the research team over a 2-week period using a comprehensive search strategy. Codes were used to categorize the content of posts to identify the frequency of content categories shared over social media platforms. Posts were evaluated by content experts to determine the frequency of posts consistent with existing research evidence. User engagement was analyzed using Netlytic, a social network analysis program, to examine visual networks illustrating the level of user engagement. RESULTS From the 2-week period, nearly 1500 pain-related and 3800 sleep-related posts were identified and analyzed. Twitter was used most often to share knowledge about child pain (639/1133, 56.40% of posts), and personal experiences for child sleep (2255/3008, 75.00% of posts). For both topics, Instagram posts shared personal experiences (53/68, 78% pain; 413/478, 86.4% sleep), Facebook group posts shared personal experiences (30/49, 61% pain; 230/345, 66.7% sleep) and Facebook pages shared knowledge (68/198, 34.3% pain; 452/1026, 44.05% sleep). Across platforms, research evidence was shared in 21.96% (318/1448) of pain- and 9.16% (445/4857) of sleep-related posts; 5.38% (61/1133) of all pain posts and 2.82% (85/3008) of all sleep posts shared information inconsistent with the evidence, while the rest were absent of evidence. User interactions were indirect, with mostly one-way, rather than reciprocal conversations. CONCLUSIONS Social media is commonly used to discuss child health, yet the majority of posts do not contain research evidence, and user engagement is primarily one-way. These findings represent an opportunity to expand engagement through open conversations with credible sources. Research and health care communities can benefit from incorporating specific information about evidence within social media posts to improve communication with the public and empower users to distinguish evidence-based content better. Together, these findings have identified potential gaps in social media communication that may be informative targets to guide future strategies for improving the translation of child health evidence over social media.

scholarly journals Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a Dutch cultural controversy on Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256696
Author(s):  
Anna Keuchenius ◽  
Petter Törnberg ◽  
Justus Uitermark
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Network Analysis ◽  
Language Processing ◽  
User Interaction ◽  
User Interactions ◽  
Online Interactions ◽  
Network Analyses ◽  
Social Media Platforms ◽  
Signed Network

Despite the prevalence of disagreement between users on social media platforms, studies of online debates typically only look at positive online interactions, represented as networks with positive ties. In this paper, we hypothesize that the systematic neglect of conflict that these network analyses induce leads to misleading results on polarized debates. We introduce an approach to bring in negative user-to-user interaction, by analyzing online debates using signed networks with positive and negative ties. We apply this approach to the Dutch Twitter debate on ‘Black Pete’—an annual Dutch celebration with racist characteristics. Using a dataset of 430,000 tweets, we apply natural language processing and machine learning to identify: (i) users’ stance in the debate; and (ii) whether the interaction between users is positive (supportive) or negative (antagonistic). Comparing the resulting signed network with its unsigned counterpart, the retweet network, we find that traditional unsigned approaches distort debates by conflating conflict with indifference, and that the inclusion of negative ties changes and enriches our understanding of coalitions and division within the debate. Our analysis reveals that some groups are attacking each other, while others rather seem to be located in fragmented Twitter spaces. Our approach identifies new network positions of individuals that correspond to roles in the debate, such as leaders and scapegoats. These findings show that representing the polarity of user interactions as signs of ties in networks substantively changes the conclusions drawn from polarized social media activity, which has important implications for various fields studying online debates using network analysis.

scholarly journals Multivariate Data Envelopment Analysis to Measure Airline Efficiency in European Airspace: A Network-Based Approach

2019 ◽  
Vol 9 (24) ◽  
pp. 5312 ◽  
Author(s):  
Ramon Hermoso ◽  
M. Pilar Latorre ◽  
Margarita Martinez-Nuñez
Keyword(s):  
Social Media ◽  
Data Envelopment Analysis ◽  
Network Analysis ◽  
Multivariate Data ◽  
Business Management ◽  
User Engagement ◽  
Data Envelopment ◽  
Input Output ◽  
Comprehensive Understanding ◽  
Network Analysis Metrics

In this paper, data envelopment analysis (DEA) is applied to exhaustively examine the efficiency of the main airline companies in the European airspace by using novel input/output parameters: business management factors, network analysis metrics, as well as social media estimators. Furthermore, we also use network analysis to provide a better differentiation among efficiency values. Results indicate that user engagement, as well as the analysis of the position within the airspace-from an operative perspective, influence the efficiency of the airline companies, allowing a more comprehensive understanding of its functioning.

scholarly journals Social Media Content About Children’s Pain and Sleep: Content and Network Analysis

10.2196/11193 ◽  
2018 ◽  
Vol 1 (2) ◽  
pp. e11193 ◽  
Author(s):  
Michelle E Tougas ◽  
Christine T Chambers ◽  
Penny Corkum ◽  
Julie M Robillard ◽  
Anatoliy Gruzd ◽  
...  
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Media Content ◽  
Children's Pain

Augmenting User Interaction Experience through Embedded Multimodal Media Agents in Social Networks

2015 ◽  
pp. 188-209 ◽  
Author(s):  
Maria Matsiola ◽  
Charalampos Dimoulas ◽  
George Kalliris ◽  
Andreas A. Veglis
Keyword(s):  
Social Media ◽  
Information And Communication Technologies ◽  
Information Exchange ◽  
User Interaction ◽  
Social Media Analytics ◽  
User Engagement ◽  
Mediated Communication ◽  
Media Technologies ◽  
Multi Agent ◽  
Content Processing

The current chapter proposes media agent and multi-agent models aiming at improving mediated communication and information exchange in social networking. Great progress has been conducted during the last decades in Information and Communication Technologies, which is also reflected in social media. The proposed models exploit the latest media technologies for the augmentation of user-interaction and contribution experience in multiple levels. Features of the suggested agent and multi-agent approaches are discussed and elaborated through the prism of social computing, social media analytics and intelligence, resulting to a sophisticated communication mediator between users and social groups. In addition, enhanced user engagement and collaboration are considered in terms of rich media experience and augmented reality, semantic interaction services, intelligent content processing and management automation over interoperable multiplatform environments. Social media cooperation and integration is envisioned towards the realization of Web 3.0 and beyond, as the main chapter contribution.

scholarly journals The FDA authorization of direct-to-consumer genetic testing for three BRCA1/2 pathogenic variants: a twitter analysis of the public’s response

JAMIA Open ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 411-415 ◽  
Author(s):  
Megan C Roberts ◽  
Caitlin G Allen ◽  
Brittany L Andersen
Keyword(s):  
Social Media ◽  
Genetic Testing ◽  
Information Exchange ◽  
Genetic Test ◽  
Direct To Consumer ◽  
Long Period ◽  
Pathogenic Variants ◽  
Personal Experiences ◽  
Genetic Technologies ◽  
Twitter Analysis

Abstract Objectives In March 2018, the Food and Drug Administration (FDA) announced its authorization of a direct-to-consumer (DTC) genetic test for three pathogenic BRCA1/2 variants. We sought to determine to whether social media discussion increased following the authorization, who was driving social media conversations, and what topics were discussed. Methods Using Crimson Hexagon, we described tweets before, during, and after the FDA announcement authorizing 23andMe to return BRCA1/2 results (3/4/18–3/10/18). We conducted qualitative coding of a subset of 605 tweets to better understand Twitter communication. Results We identified 11 055 twitter posts across the week of FDA’s announcement. Twitter discourse about 23andMe and the FDA authorization peaked the day following the FDA’s press release. Most tweets (48.6%) were informational and 26.3% were either expressing opinions (about 23andMe and/or FDA authorization, 14.9%) or testimonials (personal experiences with genetic testing, 11.4%). The types of tweets varied over the week-long period (P <  .001). Discussion Twitter discussion about the FDA’s authorization of DTC for three pathogenic BRCA1/2 variants increased immediately following the announcement. As more genetic technologies are brought to the DTC market, social media sites, like Twitter, will play a role in disseminating this information, providing a platform for information exchange, consumer testimonials, opinion pieces, and research.

scholarly journals Insights From a Text Messaging–Based Sexual and Reproductive Health Information Program in Tanzania (m4RH): Retrospective Analysis (Preprint)

2018 ◽  
Author(s):  
Patrick S Olsen ◽  
Kate F Plourde ◽  
Christine Lasway ◽  
Eric van Praag
Keyword(s):  
Reproductive Health ◽  
Text Messaging ◽  
Secondary Data ◽  
Specific Information ◽  
User Engagement ◽  
Contraceptive Methods ◽  
Main Menu ◽  
User Interactions ◽  
Specific Content ◽  
Mhealth Intervention

BACKGROUND Many mobile health (mHealth) interventions have the potential to generate and store vast amounts of system-generated participant interaction data that could provide insight into user engagement, programmatic strengths, and areas that need improvement to maximize efficacy. However, despite the popularity of mHealth interventions, there is little documentation on how to use these data to monitor and improve programming or to evaluate impact. OBJECTIVE This study aimed to better understand how users of the Mobile for Reproductive Health (m4RH) mHealth intervention engaged with the program in Tanzania from September 2013 to August 2016. METHODS We conducted secondary data analysis of longitudinal data captured by system logs of participant interactions with the m4RH program from 127 districts in Tanzania from September 2013 to August 2016. Data cleaning and analysis was conducted using Stata 13. The data were examined for completeness and “correctness.” No missing data was imputed; respondents with missing or incorrect values were dropped from the analyses. RESULTS The total population for analysis included 3,673,702 queries among 409,768 unique visitors. New users represented roughly 11.15% (409,768/3,673,702) of all queries. Among all system queries for new users, 46.10% (188,904/409,768) users accessed the m4RH main menu. Among these users, 89.58% (169,218/188,904) accessed specific m4RH content on family planning, contraceptive methods, adolescent-specific and youth-specific information, and clinic locations after first accessing the m4RH main menu. The majority of these users (216,422/409,768, 52.82%) requested information on contraceptive methods; fewer users (23,236/409,768, 5.67%) requested information on clinic location. The conversion rate was highest during the first and second years of the program when nearly all users (11,246/11,470, 98.05%, and 33,551/34,830, 96.33%, respectively) who accessed m4RH continued on to query more specific content from the system. The rate of users that accessed m4RH and became active users declined slightly from 98.05% (11,246/11,470) in 2013 to 87.54% (56,696/64,765) in 2016. Overall, slightly more than one-third of all new users accessing m4RH sent queries at least once per month for 2 or more months, and 67.86% (278,088/409,768) of new and returning users requested information multiple times per month. Promotional periods were present for 15 of 36 months during the study period. CONCLUSIONS The analysis of the rich data captured provides a useful framework with which to measure the degree and nature of user engagement utilizing routine system-generated data. It also contributes to knowledge of how users engage with text messaging (short message service)-based health promotion interventions and demonstrates how data generated on user interactions could inform improvements to the design and delivery of a service, thereby enhancing its effectiveness.

scholarly journals A Network Analysis of Information Exchange using Social Media in ICT Exhibition

2014 ◽  
Vol 20 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Ki Mok Ha ◽  
Hyun Sil Moon ◽  
Il Young Choi ◽  
Jae Kyeong Kim
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Information Exchange

Augmenting User Interaction Experience Through Embedded Multimodal Media Agents in Social Networks

2018 ◽  
pp. 1972-1993 ◽  
Author(s):  
Maria Matsiola ◽  
Charalampos Dimoulas ◽  
George Kalliris ◽  
Andreas A. Veglis
Keyword(s):  
Social Media ◽  
Information And Communication Technologies ◽  
Information Exchange ◽  
User Interaction ◽  
Social Media Analytics ◽  
User Engagement ◽  
Mediated Communication ◽  
Media Technologies ◽  
Multi Agent ◽  
Content Processing

The current chapter proposes media agent and multi-agent models aiming at improving mediated communication and information exchange in social networking. Great progress has been conducted during the last decades in Information and Communication Technologies, which is also reflected in social media. The proposed models exploit the latest media technologies for the augmentation of user-interaction and contribution experience in multiple levels. Features of the suggested agent and multi-agent approaches are discussed and elaborated through the prism of social computing, social media analytics and intelligence, resulting to a sophisticated communication mediator between users and social groups. In addition, enhanced user engagement and collaboration are considered in terms of rich media experience and augmented reality, semantic interaction services, intelligent content processing and management automation over interoperable multiplatform environments. Social media cooperation and integration is envisioned towards the realization of Web 3.0 and beyond, as the main chapter contribution.

ANALISIS PERINGKAT TOP BRAND OJEK ONLINE MENGGUNAKAN JEJARING SOSIAL PERCAKAPAN TWITTER

2019 ◽  
Vol 24 (2) ◽  
pp. 88-104
Author(s):  
Ilham Aminudin ◽  
Dyah Anggraini
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Path Length ◽  
Average Path Length ◽  
Average Degree ◽  
Clustering Coefficient ◽  
R Programming

Banyak bisnis mulai muncul dengan melibatkan pengembangan teknologi internet. Salah satunya adalah bisnis di aplikasi berbasis penyedia layanan di bidang moda transportasi berbasis online yang ternyata dapat memberikan solusi dan menjawab berbagai kekhawatiran publik tentang layanan transportasi umum. Kemacetan lalu lintas di kota-kota besar dan ketegangan publik dengan keamanan transportasi umum diselesaikan dengan adanya aplikasi transportasi online seperti Grab dan Gojek yang memberikan kemudahan dan kenyamanan bagi penggunanya Penelitian ini dilakukan untuk menganalisa keaktifan percakapan brand jasa transportasi online di jejaring sosial Twitter berdasarkan properti jaringan. Penelitian dilakukan dengan dengan mengambil data dari percakapan pengguna di social media Twitter dengan cara crawling menggunakan Bahasa pemrograman R programming dan software R Studio dan pembuatan model jaringan dengan software Gephy. Setelah itu data dianalisis menggunakan metode social network analysis yang terdiri berdasarkan properti jaringan yaitu size, density, modularity, diameter, average degree, average path length, dan clustering coefficient dan nantinya hasil analisis akan dibandingkan dari setiap properti jaringan kedua brand jasa transportasi Online dan ditentukan strategi dalam meningkatkan dan mempertahankan keaktifan serta tingkat kehadiran brand jasa transportasi online, Grab dan Gojek.

scholarly journals Exploring halal tourism tweets on social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ali Feizollah ◽  
Mohamed M. Mostafa ◽  
Ainin Sulaiman ◽  
Zalina Zakaria ◽  
Ahmad Firdaus
Keyword(s):  
Social Media ◽  
Network Analysis ◽  
Topic Modeling ◽  
Semantic Network ◽  
Word List ◽  
Global Market ◽  
Semantic Network Analysis ◽  
Tourist Destinations ◽  
Muslim Countries ◽  
Emotion Lexicon

AbstractThis study explores tweets from Oct 2008 to Oct 2018 related to halal tourism. The tweets were extracted from twitter and underwent various cleaning processes. A total of 33,880 tweets were used for analysis. Analysis intended to (1) identify the topics users tweet about regarding halal tourism, and (2) analyze the emotion-based sentiment of the tweets. To identify and analyze the topics, the study used a word list, concordance graphs, semantic network analysis, and topic-modeling approaches. The NRC emotion lexicon was used to examine the sentiment of the tweets. The analysis illustrated that the word “halal” occurred in the highest number of tweets and was primarily associated with the words “food” and “hotel”. It was also observed that non-Muslim countries such as Japan and Thailand appear to be popular as halal tourist destinations. Sentiment analysis found that there were more positive than negative sentiments among the tweets. The findings have shown that halal tourism is a global market and not only restricted to Muslim countries. Thus, industry players should take the opportunity to use social media to their advantage to promote their halal tourism packages as it is an effective method of communication in this decade.

Sign in / Sign up

Export Citation Format

Share Document