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

Adam Sage and Robert Furberg

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GRAPH API

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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 Buddy Lists Chat Rooms

Screen Scraping Personal Websites Online Encyclopedia Publishing Banner Ads

Facebook Friends Groups/Pages

APIs Blogs Wikipedia Sharing 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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GRAPH API

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GRAPH API

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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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My Facebook Network

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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?*

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Age

65+ is the fastest growing age group (150% from 2009 to 2011)

% of internet users

Statistically significant

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Who Uses Social Media?*

Statistically significant

Men Women0%

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40%

60%

80%

100%

Gender% of internet users

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Who Uses Social Media?*

% of internet users

White Black Hispanic0%

20%

40%

60%

80%

100%

Race/Ethnicity

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***

**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

*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

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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

18 - 29 30 - 49 50 - 64 65+0%

20%

40%

60%

80%

100%

Social Media Use

18 - 29 30 - 49 50 - 64 65+0%

20%

40%

60%

80%

Smartphone Ownership*

*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