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Mobile, Social, Global: Applications of Emerging Technologies in Survey Reseach


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Social Media portion of the 2012 SAPOR Short Course

Social Media portion of the 2012 SAPOR Short Course

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  • 1. RTI International Mobile, Social, Global: Applications of Emerging Technologies in Survey Research Adam Sage and Robert Furberg RTI International RTI International is a trade name of Research Triangle Institute.
  • 2. RTI International GRAPH API
  • 3. RTI International
  • 4. RTI International
  • 5. RTI International Research in a Web 2.0 World  The Evolution of the Web – 1.0 to 2.0  Dynamic and Interactive Data Environments  APIs and Data Capture  Facebook API and the Social Graph  Review of Social Networking Sites  Facebook  Surface measures (e.g., “likes,” comments, photos etc)  Surface utilities (groups, pages, polling, ads)  The Twitter API  Trend/Sentiment Analysis  Diaries  Social Science 2.0
  • 6. RTI International What is Web 2.0?  First introduced to a wide audience in 2003 at the first Web 2.0 conference  Associated with the collapse of the dot-com era  Utilizes the web as a platform for development (as oppose to releasing software with periodic updates)  User-centered design – data sources that prop up services become richer as more people use themO’reilly, Tim. 2012. “What is Web 2.0” Pp. 32-52 in The Social Media Reader edited by Michael Mandiberg NewYork and London, New York University Press..
  • 7. RTI International The Evolution of the Web Web 1.0 Web 2.0  AOL Profiles  Facebook  Buddy Lists  Friends  Chat Rooms  Groups/Pages  Screen Scraping  APIs  Personal Websites  Blogs  Online Encyclopedia  Wikipedia  Publishing  Sharing  Banner Ads  Targeted Ads
  • 8. RTI International Research in a Web 2.0 World  The internet experience is now more dynamic:  Social  Interactive  User-generated and user-sustained  The value in a Web 2.0 environment is in an application’s ability to be self-sufficient  Environments become sustainable when the data that props-up structure is created and annotated by its users (e.g., Facebook, Twitter, Wikipedia, Google Maps)
  • 9. RTI International Architectures of Participation and Communication  Learn from users/respondents/participants  Require constant monitoring and updates:  What functions are used?  What data is given and in what formats?  How can we constantly improve user engagement?  When/how is Ad Hoc Data Collection most conducive?  How will platform changes require application changes?  Functionality  New Features (e.g., Timeline, check-ins)
  • 10. RTI International Dynamic Data Environments The Facebook Example: The Facebook (2005) Buck, Stephanie. 2011. “The Evolution of the Facebook Profile" Retrieved from
  • 11. RTI International Dynamic Data Environments The Facebook Example: The Mini-feed (2006)
  • 12. RTI International Dynamic Data Environments The Facebook Example: Interaction (2007)
  • 13. RTI International Dynamic Data Environments The Facebook Example: Apps/Pages (2007 – 2009)
  • 14. RTI International Dynamic Data Environments The Facebook Example: The Redesign (2010)
  • 15. RTI International Dynamic Data Environments The Facebook Example: The Ticker (2011)
  • 16. RTI International Dynamic Data Environments The Facebook Example: Timeline (2011)
  • 17. RTI International API and the Web 2.0 culture  Application Programming Interfaces (APIs)  A defining characteristic of Web 2.0  Web Application: software coded in a web language (e.g., JavaScript) that is executable through a web browser  APIs are the access portals to richer data environments  APIs open the web and create a dynamic atmosphere  Allows web applications to communicate  Web applications can make utility of one another (e.g., sharing Tweets, Pins, or Instagram photos to Facebook)  Web applications can makes use of objects, processes etc (e.g., social gaming, quizzes, and readers)
  • 18. RTI International Applications for Data Collection  Interactive approach to data collection with opportunities to:  Administer surveys  Measure Context (Network Data)  Passively collect data (what I call “click and stream”)  Create data  Provide tasks with data collection components, much like a lab experiment  Incorporate other device functions (e.g., location, photo, video etc.)  Tap into or integrate with other APIs for additional data (e.g., Pinterest, Instagram etc.) Sage, A. J. (2012, May). Facebook Application as a Data Collection Platform. Presented at American Association for Public Opinion Research Annual Conference, Orlando, FL. Stillwell, D., & Kosinski, M. (2011). MyPersonality project. Retrieved from
  • 19. RTI International A Note on Data Types  Digital vs Digitized Data  Digital Data  Native to the platform  Occur only in a digital environment  Examples:  “Likes”  Status Updates – can have digitized components but are digital by nature  Tweets – the 140 character format is unique to the platform  Digitized Data  Native to the “real world”  Communicated through digital mediums; can have digital characteristics  Examples:  MapMyRun or DailyMile – exercise  “Tweet What You Eat” – eating behaviors  GetGlue – TV programs you watch, books you read,
  • 20. RTI International Socially-integrated Apps; “waterlogged” iPhone app;
  • 21. RTI International Facebook’s API and the Social Graph  Facebook’s Social Graph  The objects and connections inside (data)  Graph API  Gateway to the Social Graph  Rich data source (requires authorization or permissions)  Applications can be used to access Facebook’s Social Graph  Provide additional utility of Facebook by incorporating aspects of Facebook within its functionality  Plugins incorporate Facebook utility into websites  Users prefer minimal amount of usernames and passwords  Draws from social graph to streamline Web experience and create a more open and social Web
  • 22. RTI International GRAPH API
  • 23. RTI International GRAPH API
  • 24. RTI International Another Note on Data Types: Networks  Social Network data is not new, but the volume is difficult to ignore  Social Network data can provide unique insights into the processes of attitude formation and public opinion:  Allows us to quantify context  Allows us to measure some phenomena in new ways, including:  Communication patterns, information flow  Measures of influence  Social positioning (e.g., social distance, in-degrees, out-degrees)
  • 25. RTI International My Facebook Network
  • 26. RTI International Social Networking Sites  What are the different social networking sites that are “talking” to one another through APIs?  Facebook  Twitter  Google+  LinkedIn  And the other “niche” networks  Who uses them?
  • 27. RTI International Social Media Use  Facebook  955M MAUs (185M in US & Canada)  543M Mobile MAUs  552M DAUs (130M in US & Canada)  83M fake, duplicate, mis-categorized profiles  300M photos uploaded and 3.2B “likes” per day Facebook. (2012). Form 10-Q. Retrieved from
  • 28. RTI International Social Media Use (cont)  Twitter  140M active users*  140M Active Users (worldwide)  15% of internet users in US are Twitter users* *  8% are DAUs **  9% of cell owners use Twitter on a mobile device**  340M Tweets per day*  Who is Tweeting?  Younger, more urban and suburban, larger portions of minorities** * **Smith, A. and Brenner J. 2012. “Twitter Use 2012" Retrieved from
  • 29. RTI International Social Media Use (cont)  Other significant social networking sites/apps  Google+ (400M users, 100M MAUs)*  LinkedIn (175M users)**  Pinterest  Photos/Images/video  Instagram (owned by Facebook)  Youtube  Vimeo  Color  Location  FourSquare (25M users)***  Yelp  Nagivation  Waze (crowdsourced traffic updates)  Music  Spotify * ** ***
  • 30. RTI International Who Uses Social Media?* % of internet users Age 100% 80% 65+ is the fastest growing age group 60% (150% from 2009 to 2011) 40% Statistically significant 20% 0% 18 - 29 30 - 49 50 - 64 65+
  • 31. RTI International Who Uses Social Media?* % of internet users Gender 100% 80% 60% Statistically significant 40% 20% 0% Men Women
  • 32. RTI International Who Uses Social Media?* % of internet users Race/Ethnicity 100% 80% 60% 40% 20% 0% White Black Hispanic Madden, M., Zickuhr, K. 2011. “65% of online adults use social network sites” Retrieved from
  • 33. RTI International How else can social media be used?  Facebook  Surface measures  Surface utilities  Twitter  Measuring  Trends  Public Opinion  Attitudes  Behaviors  Other Web 2.0 Concepts
  • 34. RTI International How is Facebook being used for research?  Surface Measures  Status Updates  Facebook Gross National Happiness Index – not a valid measure of mood or well-being, but may play role in mood regulation*  Indicative of the potential for network analysis  Comments  Offer similar utility to status updates, but are the unique as 1 of 2 types of supplemental info for status updates  Likes  Can supplement status updates  What is the meaning of a “like?” What does it translate to?  Shares  How does content (e.g., opinions and attitudes) resonate and become viral? *Wang, N., Kosinski, M., Stillwell, D.J. & Rust, J. (2012) Can well-being be measured using Facebook status updates? Validation of Facebook’s Gross National Happiness Index. Social Indicators Research.
  • 35. RTI International How is Facebook being used for research?  Surface Utilities  Recruiting/Sample Building  Ads  Snowball*  Polls**  One question at a time  Limitations include selection bias and FB use bias  Groups as focus group environments  No known research to date, but potential exists for  Virtual, on-going focus groups with built-in measurement capabilities (e.g., polling and comments) and a historical record of interaction  Tracing*** *Bhutta, C. B. 2012. “Not by the Book: Facebook as a Sampling Frame” Sociological Methods and Research published online **Chang, J. (2010). “How Voters Turned-out of Facebook” retrieved from ***Rhodes, B.B., & Marks, E.L. (2011). “Using Facebook to locate sample members.” Survey Practice, October. Retrieved from
  • 36. RTI International Facebook Ads and Building Samples  Targeted Ads  My research indicates that for many populations, Facebook ads can be more cost efficient for developing non-probability samples*  Well-suited for recruiting convenience samples (focus groups, cognitive interviews etc.)  More “traditional” methods (e.g., Craigslist, newspapers)  Less precise and more vulnerable to “professional participants”  Check out Brian Head’s paper at SAPOR  Facebook Ads are still evolving  Ad placement is now seen in newsfeed  Mobile! *Sage, A. J., Richards, A. K., & Dean, E. F. (2012, May). Facebook Ads: An Adaptive Convenience Sample- Building Mechanism. Poster presented at American Association for Public Opinion Research Annual Conference, Orlando, FL.
  • 37. RTI International Twitter API – Trends  Trends and other pattern recognition  Tracking phenomena (via text analysis, sentiment analysis)  Tracking has revealed epidemics weeks prior to health officials*  Supplementing Surveys**  Matching against other trend data  Google  Longitudinal Surveys *Chunara, R., Andrews, J. R., and Brownstein, J. S. 2012. “Social and News Media Enabled Estimation if Epidemiological Patterns Early in the 2010 Haitian Cholera Outbreak. The American Journal of Tropical Medicine and Hygiene 86:39-45 ** Murphy, J., Kim, A., Hagood, H., Augustine, C., Kroutil., Sage, A. 2011. “Twitter Feeds and Google Search Query Surveillance: Can They Supplement Survey Data Collection?” retrieved on September 17, 2012 from
  • 38. RTI International Twitter API – Public Opinion and Attitudes  (Near) Real-time Public Opinion  Some research suggests sentiment analysis can provide information similar to polls, however limitations do exist*  50% of URLs consumed from 20K “elite” users**  Researchers have demonstrated ability to filter opinion-makers from opinion-holders*** *O’Connor, B. 2012. “From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series” presented at American Association for Public Opinion Research Annual Conference in Orlando, FL. Retrieved from **Wu, S., Hofman, J.M., Mason, M.A., Watts, D. J. 2011. “Who Says What to Whom on Twitter” presented at 20th Annual World Wide Web Conference, ACM, Hyderabad, India. Retrieved from ***Finn, S., Mustafaraj, E. 2012. “Real-Time Filtering for Pulsing Public Opinion in Social Media” presented at 25th International Florida Artificial Intelligence Research Society. Retrieved from
  • 39. RTI International Twitter API – Measuring Behaviors  Diaries*  Using #hashtags and apps, participants can Tweet and track  Attitudes  Opinions  Health  Behaviors  Moods  Limitations  140 character limit (although it could be a positive!)  Privacy *Cook, S., Richards, A., Dean, E., Haque, S. (2012). “What’s Happening? Twitter for Diary Studies” presented 67th annual American Association for Public Opinion Research (AAPOR) conference in Orlando, FL.
  • 40. RTI International Twitter API – Early Warning System  The 5.9 magnitude earthquake that originated in Mineral, Virginia  P-waves travel ~ 1,000 miles/minute  Retweets of the earthquake appeared well over 1,000 miles away within 60 seconds *Lotan, G. 2011. “All Shook Up: Mapping Earthquake News on Twitter from Virginia to Maine” Retrieved from maine.
  • 41. RTI International A Note on Wikipedia and Wikis  Wikis  Used to create and edit content in a web environment  Great example of research wiki:  Wikipedia  Crowdsourced, user-generated encyclopedia  Open sourced (anyone can edit)  The principle of many-to-many – the wisdom of the crowd  Crowd Curating  Wikis and Wikipedia are examples of how survey methodologists can utilize the knowledge of many to optimize the development and evolution of methodologies and question types
  • 42. RTI International Going Mobile  543M of Facebook’s 955M MAUs are Mobile MAUs  9% of cell owners use Twitter on a mobile device  Social Networking platforms are going mobile – FourSquare, Instagram, Waze are native to mobile – Facebook’s biggest IPO concern is monetizing mobile Social Media Use Smartphone Ownership* 100% 80% 80% 60% 60% 40% 40% 20% 20% 0% 0% 18 - 29 30 - 49 50 - 64 65+ 18 - 29 30 - 49 50 - 64 65+ *Raine, Lee. 2012. “Smartphone Ownership Update: September 2012” retrieved from
  • 43. RTI International Feel free to contact me! Adam Sage @AdamSage