Understanding Cancer-Based Networks in Twitter Using Social Network Analysis

Murthy, Dhiraj; Groß, Axel; Oliveira, Daniela

doi:10.1109/icsc.2011.51

Cited by 17 publications

(16 citation statements)

References 52 publications

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“…This research has demonstrated that the originating user and the content of the message is likely to be a significant factor in how individuals assess the validity of information. [36]. Researchers have also attempted to identify influenza outbreaks through the monitoring of Twitter for certain keywords, but have had limited success [12].…”

Section: Applied Twitter Analysismentioning

confidence: 99%

Twitter zombie

Black

Mascaro

Gallagher

et al. 2012

Proceedings of the 17th ACM International Conference on Supporting Group Work

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Social computational systems emerge in the wild on popular social networking sites like Facebook and Twitter, but there remains confusion about the relationship between social interactions and the technical traces of interaction left behind through use. Twitter interactions and social experience are particularly challenging to make sense of because of the wide range of tools used to access Twitter (text message, website, iPhone, TweetDeck and others), and the emergent set of practices for annotating message context (hashtags, reply to's and direct messaging). Further, Twitter is used as a back channel of communication in a wide range of contexts, ranging from disaster relief to watching television. Our study examines Twitter as a transport protocol that is used differently in different sociotechnical contexts, and presents an analysis of how researchers might begin to approach studies of Twitter interactions with a more reflexive stance toward the application programming interfaces (APIs) Twitter provides. We conduct a careful review of existing literature examining socio-technical phenomena on Twitter, revealing a collective inconsistency in the description of data gathering and analysis methods. In this paper, we present a candidate architecture and methodological approach for examining specific parts of the Twittersphere. Our contribution begins a discussion among social media researchers on the topic of how to systematically and consistently make sense of the social phenomena that emerge through Twitter. This work supports the comparative analysis of Twitter studies and the development of social media theories.

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Section: Applied Twitter Analysismentioning

confidence: 99%

Twitter zombie

Black

Mascaro

Gallagher

et al. 2012

Proceedings of the 17th ACM International Conference on Supporting Group Work

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“…Murthy suggested a means of employing realtime data into a data repository/data gathering application in terms of research related to cancer [11]. This novel approach provided a framework, but lacked the ability to visualize or create a user interface for sense-making when it came to harvesting data.…”

Section: Introductionmentioning

confidence: 98%

Cooperative, dynamic Twitter parsing and visualization for dark network analysis

Dudas

2013

2013 IEEE 2nd Network Science Workshop (NSW)

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Developing a network based on Twitter data for social network analysis (SNA) is a common task in most academic domains. The need for real-time analysis is not as prevalent due to the fact that researchers are interested in the analysis of Twitter information after a major event or for an overall statistical or sociological study of general Twitter users. Dark network analysis is a specific field that focuses on criminal, terroristic, or people of interest networks in which evaluating information quickly and making decisions from this information is crucial. We propose a platform and visualization called Dynamic Twitter Network Analysis (DTNA) that incorporates real-time information from Twitter, its subsequent network topology, geographical placement of geotagged tweets on a Google Map, and storage for long-term analysis. The platform provides a SNA visualization that allows the user to interpret and change the search criteria quickly based on visual aesthetic properties built from key dark network utilities with a user interface that can be dynamic, up-to-date for time critical decisions and geographic specific.

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“…In addition, health-related groups with hundreds and sometimes thousands of participants have been established on Facebook, Twitter [9,27] and dedicated forums [28]. In these online spaces, individuals contact others who have or had similar health issues [27].…”

Section: Social Media and Healthmentioning

confidence: 99%

“…In the past several years, many health-related social media sites, such as PATIENTSLIKEME [9] or CAMONI ("Similar to me", "Like me" in Hebrew) [26] have been established. In addition, health-related groups with hundreds and sometimes thousands of participants have been established on Facebook, Twitter [9,27] and dedicated forums [28].…”

Section: Social Media and Healthmentioning

confidence: 99%

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They Have Needs, They Have Goals: Using Communication Theories to Explain Health-Related Social Media Use and Health Behavior Change

Mano¹

2017

MOJPH

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Today many people use social media sites such as Facebook, Twitter and YouTube. Despite extended research on the use of social media for health-related issues, little research attention has been devoted to understanding the goals and needs behind such use and its effects on health behavior. The goal of this study is to fill this research gap by employing Uses and Gratifications theory and Media System Dependency theory. The data for this study were collected through six focus groups of internet users in Israel. The findings show that people utilize a number of social media sites for health purposes, according to specific needs and goals. These needs and goals motivate individuals to choose timing, search language and search topics and to establish criteria for assessing the quality of information and its publishers. The social media is perceived to influence health behavior on different levels.

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Understanding Cancer-Based Networks in Twitter Using Social Network Analysis

Cited by 17 publications

References 52 publications

Twitter zombie

Twitter zombie

Cooperative, dynamic Twitter parsing and visualization for dark network analysis

They Have Needs, They Have Goals: Using Communication Theories to Explain Health-Related Social Media Use and Health Behavior Change

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