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Evaluating Social Media in Extension Programming Sarah Baughman, Ph.D. eXtension Sarah Baughman, Ph.D. & Brigitte Scott, Ph.D. Military Families Learning Network Virginia Tech National Association of Extension Program and Staff Development Professionals October 21, 2014

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Evaluating Social Media in Extension Programming

Sarah Baughman, Ph.D.eXtension

Sarah Baughman, Ph.D. & Brigitte Scott, Ph.D.Military Families Learning NetworkVirginia Tech

National Association of Extension Program and Staff Development Professionals October 21, 2014

Photo credit: Douglas Wrey on http://www.geek.com/wp-content/uploads/2012/02/social_media_donut.jpg

Ways to Use Social Media

Ways to Use Social Media

Annual Report from Calgary Zoo

Evaluating a “stand alone” social media campaign: Ohio State Kitchen & Campus Dairy Campaign, Jamie Seger

Theory of Change

Invest Resources

Program Activities

Increase consumption

of fruits & vegetables

Invest Resources

Program Activities

Increase consumption of fruits

& vegetables

Provide educational material on

nutrition

Maintain a food log

Enlist the support of

family

Nutritio

n Information

• Support F2F workshops with information on Facebook

• Use a FB page to encourage discussion on educational information presented F2F

Food

Log

• Provide FB incentives for person who increases the most or tries something new

• Have participants each take a different day to share one recipe they have tried or something from their food log that is working (or maybe not working)

Family

Suppor

t

• Invite family members to the FB page to encourage participants

• Highlight a different family member every week and how they have helped support healthier eating

Conversion

Engagement

Reach

Where’s the Data? Resources for Measuring and Evaluating Social Media

Facebook Insights

Twitter Tweetreach Hootsuite Tweepsmap Buffer Mentionmapp

Pinterest Tailwind

Multiplatform Sproutsocial SimplyMeasured SumAll Google Analytics

Evaluation Keys

Clear purpose

Clear goals

Consistent metrics and measurement over time

Use the measurement data to learn and improve

Contact Information

Sarah Baughman 540-231-7142 [email protected] @programeval Gplus.to/SarahBaughman Scoop it: Cooperative Extension Evaluation Pinterest.com/sarahbaughman

Getting to the Why behind the Numbers

CC by 3.0

You are already doing qualitative analysis.

CC by 3.0

From TweetReach….

From Facebook Insights….

Photo by LauraGilchrist4 - Creative Commons Attribution-NonCommercial-ShareAlike License https://www.flickr.com/photos/76060406@N07 Created with Haiku Deck

Basic Text Analysis

Basic Text Analysis: Inductive

Use data to discover concepts, themes, or models

Basic Text Analysis: Inductive

Use data to discover concepts, themes, or models

Evaluator as interpreter; highly involved

Basic Text Analysis: Inductive

Use data to discover concepts, themes, or models

Evaluator as interpreter; highly involved

Emergent, “bottom up”

Basic Text Analysis: Inductive

Use data to discover concepts, themes, or models

Evaluator as interpreter; highly involved

Emergent, “bottom up”

Qualitative outcome: key themes or categories relevant to evaluation/research questions

Application: Inductive Analysis

Facebook posts

Tweetchats or hashtags

Blog posts

LinkedIn discussions

Basic Inductive Analysis: 5 Steps

Step 1. Collect your raw data

Step 2. Read. And Read Again.

And:

Get organized!

Step 3. Create and Apply Codes (Repeat.)

Step 4. Refine Codes to Reduce Overlap

Step 5. Create Categories

Narrative Analysis (Step 6, Really.). .

Basic Text Analysis: Deductive

Data is analyzed according to prior assumptions

Basic Text Analysis: Deductive

Data is analyzed according to prior assumptions

Evaluator is “independent” from data

Basic Text Analysis: Deductive

Data is analyzed according to prior assumptions

Evaluator is “independent” from data

A-priori; “top down”

Basic Text Analysis: Deductive

Data is analyzed according to prior assumptions

Evaluator is “independent” from data

A-priori; “top down”

Quantitative outcome: metrics relevant to evaluation/research objectives

Application: Deductive Analysis

Category comparison, comparison over time Analyzing webinar chat pods Analyzing how a hashtag is leveraged in

Tweets Facebook/LinkedIn audience

engagement

Basic Deductive Analysis: 4 Steps

1.Develop data categories.

2.Clearly define those categories.

3.Read through all raw data and apply categories.

4.Count.

Chat Pod Engagement Metrics

Unique chat pod participants

Resources shared by participants

Resources shared by MFLN

Participant questions

Unique participant to participant exchanges

0 5 10 15 20 25

21

0

17

10

5

The fine print….

Only DCO viewers can participate in the chat pod; percentage of chat pod participants based on total number of DCO viewers and total number of unique participants.

Resources shared by participants include shared links, authors, studies, books, etc.; demonstrates high-level engagement because participants are contributing to the co-construction of knowledge during webinar.

Resources shared by MFLN include links, peer-reviewed studies and books, etc., from both MFLN and non-MFLN authors; demonstrates direct CA engagement with participants by further supporting and contextualizing knowledge construction by situating webinar presentation within the larger disciplinary area.

Participant questions are those listed in the chat pod; demonstrates intent to pursue two-way engagement in webinar and therefore high-level engagement.

Unique participant to participant exchanges are those in which chat pod participants respond directly to one another’s comments; demonstrates high-level engagement through realized reactive (two-way) and interactive (dependent) discourse patterns.

Chat pod text related to webinar content is not captured as an engagement measure due to its discursive category as declarative (one-way) communication. (It is noted, however, that declarative text is still understood to indicate webinar engagement, and MFLN encourages and values such participant engagement.)

Chat pod text related to technical issues and/or CEUs is not included in MFLN evaluation.

Storytelling

Storytelling

Identify narratives that connect to your evaluation aims

Storytelling

Identify narratives that connect to your evaluation aims

Be strategic and leverage stories for evaluation task at hand

Storytelling

Identify narratives that connect to your evaluation aims

Be strategic and leverage stories for evaluation task at hand

Contextualize your stories with other data to show a larger picture

Storytelling

Identify narratives that connect to your evaluation aims

Be strategic and leverage stories for evaluation task at hand

Contextualize your stories with other data to show a larger picture

Ethics, ethics, ethics

Storytelling: How?

Watch for stories

ASK for stories

Tell your own stories

From the Master Gardeners…

“On a Celebrex commercial a guy is shown bent over in some beets or chard and he raises up with a beautiful eggplant! The first time I laughed at it my wife thought I was crazy.”

Application: Storytelling and Evaluation

Use stories in your reports, and include an executive summary of those stories

Incorporate compelling stories with facts and figures

Include stories with direct quotes in press releases, on Web sites

Include stories and quotes in newsletters, brochures, annual reports

Larger Considerations

Larger Considerations

Reflexivity

Transparency

Credibility

Ethics

Contact Information

Brigitte Scott

540-231-3990

[email protected]

@4ed_eval