The document discusses using emerging technologies like social media and mobile devices in survey research. It provides an overview of the evolution of the web from Web 1.0 to the more dynamic Web 2.0. Web 2.0 allows for interactive data through application programming interfaces (APIs) that give access to social media platforms. The document then focuses on Facebook and its API, which provides access to data on users' social networks. Finally, potential uses of social media data for research purposes are discussed, including analyzing trends on Twitter, measuring attitudes through sentiment analysis, and using Facebook for recruitment and surface measures.
Mobile, Social, Global: Applications of Emerging Technologies in Survey Reseach
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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. www.rti.org
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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
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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 them
O’reilly, Tim. 2012. “What is Web 2.0” Pp. 32-52 in The Social Media Reader edited by Michael Mandiberg New
York and London, New York University Press..
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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
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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)
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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)
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Dynamic Data Environments
The Facebook Example: The Facebook (2005)
Buck, Stephanie. 2011. “The Evolution of the Facebook Profile" Retrieved from
http://mashable.com/2011/09/22/facebook-profile-evolution/#270432011--Ticker.
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Dynamic Data Environments
The Facebook Example: The Mini-feed (2006)
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Dynamic Data Environments
The Facebook Example: Interaction (2007)
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Dynamic Data Environments
The Facebook Example: Apps/Pages (2007 – 2009)
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Dynamic Data Environments
The Facebook Example: The Redesign (2010)
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Dynamic Data Environments
The Facebook Example: The Ticker (2011)
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Dynamic Data Environments
The Facebook Example: Timeline (2011)
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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)
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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
http://www.mypersonality.org/wiki/doku.php
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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,
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Socially-integrated Apps
www.tweetwhatyoueat.com; “waterlogged” iPhone app; www.dailymile.com
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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
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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)
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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?
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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
http://www.sec.gov/Archives/edgar/data/1326801/000119312512325997/d371464d10q.htm#tx371464_14
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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**
*www.twitter.com
**Smith, A. and Brenner J. 2012. “Twitter Use 2012" Retrieved from
http://www.pewinternet.org/~/media//Files/Reports/2012/PIP_Twitter_Use_2012.pdf.
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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
*https://plus.google.com/u/0/+VicGundotra/posts/2YWhK1K3FA5
**http://press.linkedin.com/about
***https://foursquare.com/about/
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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+
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Who Uses Social Media?*
% of internet users Gender
100%
80%
60%
Statistically
significant
40%
20%
0%
Men Women
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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
http://pewinternet.org/~/media//Files/Reports/2011/PIP-SNS-Update-2011.pdf
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How else can social media be used?
Facebook
Surface measures
Surface utilities
Twitter
Measuring
Trends
Public Opinion
Attitudes
Behaviors
Other Web 2.0 Concepts
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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.
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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 http://smr.sagepub.com/content/early/2012/03/19/0049124112440795.full.pdf+html
**Chang, J. (2010). “How Voters Turned-out of Facebook” retrieved from
http://www.facebook.com/notes/facebook-data-team/how-voters-turned-out-on-facebook/451788333858
***Rhodes, B.B., & Marks, E.L. (2011). “Using Facebook to locate sample members.” Survey Practice, October.
Retrieved from http://surveypractice.wordpress.com/2011/10/24/using-facebook-to-locate-sample-members/
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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.
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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
http://www.rti.org/pubs/twitter_google_search_surveillance.pdf
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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
www.brecocon.com
**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
http://research.yahoo.com/pub/3386
***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
http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS12/paper/viewFile/4459/4762
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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.
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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
http://blog.socialflow.com/post/7120244132/all-shook-up-mapping-earthquake-news-on-twitter-from-virginia-to-
maine.
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A Note on Wikipedia and Wikis
Wikis
Used to create and edit content in a web environment
Great example of research wiki:
http://mypersonality.org/wiki/doku.php
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
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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
http://pewinternet.org/Reports/2012/Smartphone-Update-Sept-2012/Findings.aspx
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Feel free to contact me!
Adam Sage
asage@rti.org
@AdamSage
www.linkedin.com/in/adamsage
www.facebook.com/mradamsage