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Pharma gets social: Top-10 pharma social media firsts in 2013

Pharma gets social: Top-10 pharma social media firsts in 2013 | healthcare technology | Scoop.it

As 2013 draws to a close, Daniel Ghinn has put together a list of his top-ten favourite pharma social media 'firsts' of the year - new things that pharmaceutical companies have been doing in social media.

It's been a year packed with new ideas, channels, and lessons learned. 


In pharma social media, this list is where the new ground is being taken in what is still a challenging environment for regulated pharmaceutical industry.

Here's what pharma did for the first time in 2013:


10. Cleaned up its Twitter name


9. Implemented Tumblr to support patients


8. Exceeded 7 million views on YouTube


7. Reached 90,000 likes on Facebook


6. Integrated social media with a prescription product website


5. Lost $160m in a social media crisis


4. Maximised congress activity with social media


3. Hosted disease-focused chats on Twitter


2. Trained doctors in social media


1. Activated Digital Opinion Leaders


To read in detail about each of the above, check out the original post at http://www.pharmaphorum.com/articles/pharma-gets-social-top-10-pharma-social-media-firsts-in-2013

Leo J. Bogee III's curator insight, December 17, 2013 8:52 PM

$160 million gone over a doctor shared misinformation via a 140-character post on Chinese social media site Sina Weibo.  The Power of Social Media.

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Tweeting For Public Health: Tracking Food Poisoning Via Social Media

Tweeting For Public Health: Tracking Food Poisoning Via Social Media | healthcare technology | Scoop.it

Can Twitter be mined for information on food poisoning outbreaks? One Google data scientist thinks so. Adam Sadilek led a team at the University of Rochester that developed Nemesis , a machine learning system which asks "which restaurants should you avoid today?"


Using a set of keywords, Nemesis mines Twitter for geolocated posts that could be indicative of foodborne illness. In tests, tweets from New York were datamined and had metadata added indicating restaurants within 25 meters that were open at the time the user tweeted. A team of humans recruited via Mechanical Turk then came up with 27 words and phrases indicating food poisoning--things like "My tummy hurts," "stomachache," "throw up," "Mylanta," and "Pepto-Bismol." Nemesis then assigned health scores to the nearby restaurants based on the proportion of food poisoning-inferring tweets.

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