Social Media and Healthcare
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Social Media and Healthcare
Articles and Discussions on the  intersection of Social Media and Healthcare. Relevant to Healthcare Practitioners, Pharma', Insurance, Clinicians, Labs, Health IT Vendors, Health Marketeers, Health Policy Makers, Hospital Administrators.
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The Science of Getting New Twitter Followers

The Science of Getting New Twitter Followers | Social Media and Healthcare | Scoop.it

Follower count is, unanimously, the biggest indicator of success on Twitter. Some people may contend with that statement. They may argue that quality of followers, quality of tweets, level of engagement, etc. are far more important success metrics.  


However, a lot of people are, without a doubt, influenced by the number of followers somebody has. Having a huge follower count is kind of a self-fulfilling prophecy. People see you have a lot of followers, assume your tweets must be extra-special or you must be extra-special and follow you, thus increasing your follower count further.  


So, what really gets you more followers? You will find articles aplenty online that tell you how to get more followers on Twitter. Why, I have written quite a few myself.   


But this post is different.  


This post does not rely on experience, observation, commonly held beliefs, guesswork or any other abstract factors to tell you where Twitter followers come from and how to get and keep them. This post is based entirely on scientific analysis and facts – numbers, stats, hard-to-refute conclusions. So, let’s get going.  


Scientifically, these are the factors that influence how many twitter followers a particular account can amass:  

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Social Media Can Boost Disease Outbreak Monitoring, Study Finds

Social Media Can Boost Disease Outbreak Monitoring, Study Finds | Social Media and Healthcare | Scoop.it

Monitoring social media websites like Twitter could help health officials and providers identify in real time severe medical outbreaks, allowing them to more efficiently direct resources and curb the spread of disease, according to a San Diego State University studypublished last month in the Journal of Medical Internet Research,Medical News Today reports.


Study Details


For the study, lead researcher and San Diego State University geography professor Ming-Hsiang Tsou and his team used a program to monitor tweets that originated within a 17-mile radius of 11 cities. The program recorded details of tweets containing the words "flu" or "influenza," including:


  • Origin;
  • Username;
  • Whether the tweet was an original or a retweet; and
  • Any links to websites in the tweet.


Researchers then compared their findings with regional data based on CDC's definition of influenza-like illness.

The program recorded data on 161,821 tweets that included the word "flu" and 6,174 tweets that included the word "influenza" between June 2012 and the beginning of December 2012.


According to the study, nine of the 11 cities exhibited a statistically significant correlation between an uptick in the number of tweets mentioning the keywords and regional outbreak reports. In five of the cities -- Denver, Fort Worth, Jacksonville, San Diego and Seattle -- the algorithm noted the outbreaks sooner than regional reports.

Drew Hodges's curator insight, February 19, 2015 5:50 PM

This is a cool article to show the real life change that social media is creating. Before it was stated that it would take up to two weeks to detect an outbreak of a disease but now with social media it can be done in a day. 

This article really shows how social media is becoming a part of our everyday life and is taking on roles that we probably didn't expect it to. 

However with the number of users increasing it is important to have tools that help us monitor the large amount of data that is present. 

Its no good having all this information if we cannot harness it's true potential, like the one illustrated in this article for disease break out.

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How Twitter can be used to address specific health issues

How Twitter can be used to address specific health issues | Social Media and Healthcare | Scoop.it

A new study led by Jenine K. Harris, PhD, examined the use of the hashtag #childhoodobesity in tweets to track Twitter conversations about the issue of overweight kids.


The study noted that conversations involving childhood obesity on Twitter don't often include comments from representatives of government and public health organizations that likely have evidence relating to how best to approach this issue. The authors think maybe they should.


Twitter use is growing nationwide. In its 2014 Twitter update, the Pew Research Center found that Twitter is used more by those in lower-income groups, which traditionally are more difficult to reach with health information.


While younger Americans also are more likely to use Twitter, it is used equally across education groups and is used more by non-white Americans than whites.


This, Harris said, is one of the reasons Twitter is an avenue that the academic and government sources with accurate health information should consider taking advantage of in order to reach a wide variety of people.


"I think public health so far doesn't have a great game plan for using social media, we're still laying the foundation for that," she said. "We're still learning what works.


"Public health communities, politicians, and government sources -- people who really know what works -- should join in the conversation. Then we might be able to make an impact," she said.

more at http://www.sciencedaily.com/releases/2014/07/140710151723.htm


askdrmaxwell's curator insight, July 14, 2014 6:09 PM

Do you use social media for your health questions and research? 

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An Exploratory Infodemiology Study on Electronic Word of Mouth on #Twitter About Physical Activity in the US

An Exploratory Infodemiology Study on Electronic Word of Mouth on #Twitter About Physical Activity in the US | Social Media and Healthcare | Scoop.it

Twitter is a widely used social medium. However, its application in promoting health behaviors is understudied.


In order to provide insights into designing health marketing interventions to promote physical activity on Twitter, this exploratory infodemiology study applied both social cognitive theory and the path model of online word of mouth to examine the distribution of different electronic word of mouth (eWOM) characteristics among personal tweets about physical activity in the United States.


This study used 113 keywords to retrieve 1 million public tweets about physical activity in the United States posted between January 1 and March 31, 2011. A total of 30,000 tweets were randomly selected and sorted based on numbers generated by a random number generator. Two coders scanned the first 16,100 tweets and yielded 4672 (29.02%) tweets that they both agreed to be about physical activity and were from personal accounts. Finally, 1500 tweets were randomly selected from the 4672 tweets (32.11%) for further coding. After intercoder reliability scores reached satisfactory levels in the pilot coding (100 tweets separate from the final 1500 tweets), 2 coders coded 750 tweets each. Descriptive analyses, Mann-Whitney U tests, and Fisher exact tests were performed.


Results: Tweets about physical activity were dominated by neutral sentiments (1270/1500, 84.67%). Providing opinions or information regarding physical activity (1464/1500, 97.60%) and chatting about physical activity (1354/1500, 90.27%) were found to be popular on Twitter.


Approximately 60% (905/1500, 60.33%) of the tweets demonstrated users’ past or current participation in physical activity or intentions to participate in physical activity. However, social support about physical activity was provided in less than 10% of the tweets (135/1500, 9.00%). Users with fewer people following their tweets (followers) (P=.02) and with fewer accounts that they followed (followings) (P=.04) were more likely to talk positively about physical activity on Twitter.


People with more followers were more likely to post neutral tweets about physical activity (P=.04). People with more followings were more likely to forward tweets (P=.04). People with larger differences between number of followers and followings were more likely to mention companionship support for physical activity on Twitter (P=.04).


Conclusions: Future health marketing interventions promoting physical activity should segment Twitter users based on their number of followers, followings, and gaps between the number of followers and followings.


The innovative application of both marketing and public health theory to examine tweets about physical activity could be extended to other infodemiology or infoveillance studies on other health behaviors (eg, vaccinations).


more at http://www.jmir.org/2013/11/e261/

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