Building Apps for Social Science Research

Chris Bail, Duke University
SICSS, Day 2

Salganik's list of the weaknesses of digital trace data:

 

Incomplete
Inaccessible
Non-Representative
Drifting
Algorithmic Confounding
Dirty
Sensitive

But what are the alternatives?

 

But what are the alternatives?

 

-Survey response rates continue to drop

But what are the alternatives?

 

-Survey response rates continue to drop

-Many of the most important questions require longitudinal/relational/qualitative data

But what are the alternatives?

 

-Survey response rates continue to drop

-Many of the most important questions require longitudinal/relational/qualitative data

-Digital trace data have a number of major advantages that conventional sources do not (big, always on, non-reactive)

Can we have our cake and eat it too?

Apps can Help Us Address Many of the limitations of digital trace data

 

Incomplete
Inaccessible
Non-Representative
Drifting
Algorithmic Confounding
Dirty
Sensitive

Social Media Survey Apps (SMSAs)

 

Social Media Survey Apps (SMSAs)

 

A Social Media Survey App is a web or mobile-based tool built by a researcher in order to:

Social Media Survey Apps (SMSAs)

 

A Social Media Survey App is a web or mobile-based tool built by a researcher in order to:

a) collect public and/or private data produced by social media users from an API;

Social Media Survey Apps (SMSAs)

 

A Social Media Survey App is a web or mobile-based tool built by a researcher in order to:

a) collect public and/or private data produced by social media users from an API;

b) collect supplemental information from such users (e.g. demographics) using more conventional survey methods;

Social Media Survey Apps (SMSAs)

 

A Social Media Survey App is a web or mobile-based tool built by a researcher in order to:

a) collect public and/or private data produced by social media users from an API;

b) collect supplemental information from such users (e.g. demographics) using more conventional survey methods;

c) offer something back to the user as an incentive to share their data (e.g. analysis or financial incentives)

Workflow of a Social Media Survey App

Example: The Viralgorithm

Actual Workflow of the Viralgorithm

Data Collection Process

 

Response Rate

 

  1. Approximately 40% of all organizations contacted installed the app (across two fields)

Minimal Evidence of Selection

Challenges of Building Apps for Social Science Research

 

Challenges of Building Apps for Social Science Research

 

  1. Significant coding skills required (html, css, cloud-computing, reactive programming)

Challenges of Building Apps for Social Science Research

 

  1. Significant coding skills required (html, css, cloud-computing, reactive programming)

  2. Competitive environment for attention (apps are no longer “new”)

Challenges of Building Apps for Social Science Research

 

  1. Significant coding skills required (html, css, cloud-computing, reactive programming)

  2. Competitive environment for attention (apps are no longer “new”)

  3. Concerns about data sharing/privacy

Challenges of Building Apps for Social Science Research

 

  1. Significant coding skills required (html, css, cloud-computing, reactive programming)

  2. Competitive environment for attention (apps are no longer “new”)

  3. Concerns about data sharing/privacy

  4. Compelling incentives are hard to identify- and particularly challenging for studies of sensitive topics.

SHINY

What is Shiny?

Shiny is a (relatively) new tool that enables people to build, compile, and host interactive apps natively within RStudio

A Simple Shiny App

Three Components of A Shiny App

 

Global.R
server.R
ui.R

Global.R

 

-The “memory” of the app. Stores things you want to call from other parts of the app (usually data but could also be functions and other types of objects)

server.R

 

-The “brains” of the app- runs the analysis you want to show the user, but can also store data generated by the user, or expose different users to different types of information (good for experimentation)

ui.R

 

-The “face” of the app. Determines what user will see (e.g. what types of visualizations, check boxes or word boxes, fonts, etc.) Can load fancy images, logos, etc. to improve the overall appeal of the app.

Shiny Templates

 

There are now many Shiny apps out there. Check out the templates (with code) here.

Linking to Cloud Servers

 

-Check out the googledrive package for loading and storing data.

-High-volume app hosting is available via RStudio.

AFTER LUNCH GROUP EXERCISE: DESIGN A RESEARCH PROJECT THAT USES DIGITAL TRACE DATA

Group Exercise (Until 4PM)

Group Exercise (Until 4PM)

1) Reintroduce yourselves (name, Discipline, 2-3 Sentences about your research)

Group Exercise (Until 4PM)

1) Reintroduce yourselves (name, Discipline, 2-3 Sentences about your research)

2) 5 minute individual exercise: Each person comes up with a research design using digital trace data to examine one of the other people in the group's research interests

Group Exercise (Until 4PM)

1) Reintroduce yourselves (name, Discipline, 2-3 Sentences about your research)

2) 5 minute individual exercise: Each person comes up with a research design using digital trace data to examine one of the other people in the group's research interests

3) Present each research design (1 minute each)

Group Exercise (Until 4PM)

1) Reintroduce yourselves (name, Discipline, 2-3 Sentences about your research)

2) 5 minute individual exercise: Each person comes up with a research design using digital trace data to examine one of the other people in the group's research interests

3) Present each research design (1 minute each)

4) Pick one of the research designs to develop into a very brief proposal that includes a) a research question; b) a research methodology

Group Exercise (Until 4PM)

1) Reintroduce yourselves (name, Discipline, 2-3 Sentences about your research)

2) 5 minute individual exercise: Each person comes up with a research design using digital trace data to examine one of the other people in the group's research interests

3) Present each research design (1 minute each)

4) Pick one of the research designs to develop into a very brief proposal that includes a) a research question; b) a research methodology

5) Five minute presentations from each group

We are all responsible for the success of SICSS!

 

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