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Future Data Collection CARMA Internet Research Module Jeff Stanton

Carma internet research module: Future data collection

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Page 1: Carma internet research module: Future data collection

Future Data Collection

CARMA Internet Research ModuleJeff Stanton

Page 2: Carma internet research module: Future data collection

Several Promising Environments and Techniques

• Visual Surveys• Audio and video interviewing• Virtual Worlds• Web scraping• Network extraction and mapping• Polls Everywhere• Mobility

Page 3: Carma internet research module: Future data collection

Visual SurveysVisual DNA: http://www.visualdna.com/Also try: http://www.youniverse.com/

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Visual Surveys

Provides an engaging alternative to text-based surveys; more fun for respondents

Requires considerable set-up time; each screen is like an item; each picture is like an item response; every item and response must be keyed against one or more criteriaExample: Previous page, “How do you approach

stress,” could be keyed against other subjective or objective measures of stress, coping, general health, immune response, etc.

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Audio and Video Interviewing

Methods: Structured, semi-structured, and unstructured interviewing; focus groups

Products: Skype, WebEx, Adobe Connect, Cisco Telepresence

Advantages: Reduced travel costs, speed

Disadvantages: High bandwidth,user technology requirements, unreliable connections

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Virtual Worlds

VastPark: http://www.vastpark.com/

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Virtual Worlds

Combine text and audio chat with social networking and 3D model building

Methods: Structured, semi-structured, and unstructured interviewing; focus groups; unobtrusive observation; participant observation; possibly some experimental perceptual, cooperative, or navigational tasks

Products: VastPark, OpenSim, EduSim, TeleplaceAdvantages: Speed, low costDisadvantages: Steep learning curve; high bandwidth;

user technology requirements; unreliable connections

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Web Scraping

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Web Scraping

Retrieval and processing of text or images, e.g., from blogs; processing may include semantic analysis of people, events, emotions

Methods: Archival document analysisProducts: 100s of commercial, mainly focused on brand,

reputation, marketing; open source product: WebHarvestAdvantages: Data are plentiful and cover a wide range of

topicsDisadvantages: Technology hard to master; even after

considerable automated processing, analysis has an intensive, qualitative flavor

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Network Mapping

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Mapping Social Networks

Nicholas Christakis of the Framingham Heart Study has shown the power of social networks to influence a variety of health outcomes

Methods: Traditional self-report & objective measures; topographical measures such as network centrality; “neighbor” measures

Products: Depends on data types; TouchGraph is a network web search engine; InFlow; UCInet; See: http://en.wikipedia.org/wiki/Social_network_analysis_software

Advantages: Meaningful improvement in predictive capabilityDisadvantages: Intensive technique requires careful planning and

setup

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Facebook Polls

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Embedded Polls

Collection of short-format survey data from social networking and membership sites

Methods: Primarily standard, closed-ended self-report; single item scales

Products: Example: Vizu provides a “widget” that allows embedding of polls on Facebook pages

Advantages: Quick, cheap, possible to get a large sample in a short time

Disadvantages: Difficult to control access, short format limits use of multi-item scales

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Mobility

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Data Collection from Mobile Devices

Using smartphones and other mobile devices as a basis for interacting with participants

Methods: Primarily self-report but can include location and movement data

Products: Example: Survey On The Spot allows location aware surveys to be delivered to smart phones; TrailGuru collects route data from hikers and joggers

Advantages: Platform is becoming ubiquitous, location data provides new options for understanding behavior

Disadvantages: Privacy issues, small screen, complex programming interfaces