Twitter and Non-Elites: Interpreting Power Dynamics in the Life Story of the (#)BRCA Twitter Stream
نویسنده
چکیده
In May 2013 and March 2015, actress Angelina Jolie wrote in the New York Times about her choice to undergo preventive surgery. In her two op-eds, she explained that - as a carrier of the BRCA1 gene mutation - preventive surgery was the best way to lower her heightened risk of developing breast and ovarian cancer. By applying a digital methods approach to BRCA-related tweets from 2013 and 2015, before, during, and after the exposure of Jolie's story, this study maps and interprets Twitter discursive dynamics at two time points of the BRCA Twitter stream. Findings show an evolution in curation and framing dynamics occurring between 2013 and 2015, with individual patient advocates replacing advocacy organizations as top curators of BRCA content and coming to prominence as providers of specialist illness narratives. These results suggest that between 2013 and 2015, Twitter went from functioning primarily as an organization-centered news reporting mechanism, to working as a crowdsourced specialist awareness system. This article advances a twofold contribution. First, it points at Twitter's fluid functionality for an issue public and suggests that by looking at the life story-rather than at a single time point-of an issue-based Twitter stream, we can track the evolution of power roles underlying discursive practices and better interpret the emergence of non-elite actors in the public arena. Second, the study provides evidence of the rise of activist cultures that rely on fluid, non-elite, collective, and individual social media engagement.
منابع مشابه
A Model for Detecting of Persian Rumors based on the Analysis of Contextual Features in the Content of Social Networks
The rumor is a collective attempt to interpret a vague but attractive situation by using the power of words. Therefore, identifying the rumor language can be helpful in identifying it. The previous research has focused more on the contextual information to reply tweets and less on the content features of the original rumor to address the rumor detection problem. Most of the studies have been in...
متن کاملA High-Performance Model based on Ensembles for Twitter Sentiment Classification
Background and Objectives: Twitter Sentiment Classification is one of the most popular fields in information retrieval and text mining. Millions of people of the world intensity use social networks like Twitter. It supports users to publish tweets to tell what they are thinking about topics. There are numerous web sites built on the Internet presenting Twitter. The user can enter a sentiment ta...
متن کاملExamination of Emergency Medicine Physicians’ and Residents’ Twitter Activities During the First Days of the COVID-19 Outbreak
Introduction: Social media has become an important element of interaction and found itself a place in every aspect of our lives. This study examined the twitter activities of emergency medicine physicians and residents (EMP&R;) about the COVID-19 outbreak. Methods: The study concentrated on Twitter, a major social media network. To identify accounts owned ...
متن کاملDetection of Twitter Users' Attitudes about Flu Vaccine based on the Content and Sentiment Analysis of the Sent Tweets
Introduction: The influenza vaccine is one of the controversial challenges in today's societies. Considering the importance of using the flu vaccine in preventing the spread of influenza virus, the Twitter network, as a rich source of data, provides suitable conditions for research in this field to examine the attitudes of different people about this vaccine. The results in one hand will help h...
متن کاملReview of “Twitter and Jihad: The Communication Strategy of ISIS” edited by Monica Maggioni and Paolo Magri
Twitter and Jihad: The Communication Strategy of ISIS edited by Monica Maggioni & Paolo Magri. Milan, Italy: ISPI, 2015. 168pp., $10 (p/b), ISBN 978-88-98014-66-8
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 3 شماره
صفحات -
تاریخ انتشار 2017