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


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Social Media portion of the 2012 SAPOR Short Course

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

  1. 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. 2. RTI International GRAPH API
  3. 3. RTI International
  4. 4. RTI International
  5. 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. 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. 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. 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. 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. 10. RTI International Dynamic Data Environments The Facebook Example: The Facebook (2005) Buck, Stephanie. 2011. “The Evolution of the Facebook Profile" Retrieved from
  11. 11. RTI International Dynamic Data Environments The Facebook Example: The Mini-feed (2006)
  12. 12. RTI International Dynamic Data Environments The Facebook Example: Interaction (2007)
  13. 13. RTI International Dynamic Data Environments The Facebook Example: Apps/Pages (2007 – 2009)
  14. 14. RTI International Dynamic Data Environments The Facebook Example: The Redesign (2010)
  15. 15. RTI International Dynamic Data Environments The Facebook Example: The Ticker (2011)
  16. 16. RTI International Dynamic Data Environments The Facebook Example: Timeline (2011)
  17. 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. 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. 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. 20. RTI International Socially-integrated Apps; “waterlogged” iPhone app;
  21. 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. 22. RTI International GRAPH API
  23. 23. RTI International GRAPH API
  24. 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. 25. RTI International My Facebook Network
  26. 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. 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. 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. 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. 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. 31. RTI International Who Uses Social Media?* % of internet users Gender 100% 80% 60% Statistically significant 40% 20% 0% Men Women
  32. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 43. RTI International Feel free to contact me! Adam Sage @AdamSage