Social Media and Nonprofits: Measurement

A few good tips

Profile of the work that SumAll is doing 

Here's another resource for finding data nerds who can work with nonprofits! 

We have a different sort of solution in mind – one that harnesses the untapped potential of students. As institutions of higher education dramatically expand their data science offerings, countless students are gaining new skills, but aren’t putting them to use with real-world datasets. Next month, we’re giving tens of thousands of those students from around the world the chance to do something more exciting: work with your data to strengthen your impact.

Nonprofits of all types are now invited to apply to “Introduction to Data Science,” a massively open online course to be taught next month by Prof. Bill Howe of the University of Washington. As part of the course, students will have the option to complete a project in which they work with a real dataset to address the needs of an organization. As they learn techniques in data visualization and trend identification, these students will apply what they learn to help drive your organization’s future initiatives. The insights they offer could strengthen your impact and identify areas for growth.

In a world with limited resources, it just makes sense to utilize student talents and creativity to strengthen your work. Tens of thousands of students have already registered for the course – don’t miss your chance to recruit thei

Humerous but good overview of big data from point of view of vendor

The number of twitter followers is not a measure of success ...http://bits.blogs.nytimes.com/2013/04/25/researchers-call-out-twitter-celebrities-with-suspicious-followings/

The first three metrics refer to “the number of articles produced … during a given time period, an average length of an article [and] the importance of coverage from the news source.” These favor large publishers, but they select for originality and focus as well. Google is actually “counting the number of original sentences” and comparing the output about the given subject to the news source’s competitors.

Some video measurement advice 

But is big data really all it's cracked up to be? Can we trust that so many ones and zeros will illuminate the hidden world of human behavior? Foreign Policy invited Kate Crawford of the MIT Center for Civic Media to go behind the numbers:

"With Enough Data, the Numbers Speak for Themselves."

Not a chance. The promoters of big data would like us to believe that behind the lines of code and vast databases lie objective and universal insights into patterns of human behavior, be it consumer spending, criminal or terrorist acts, healthy habits, or employee productivity. But many big-data evangelists avoid taking a hard look at the weaknesses. Numbers can't speak for themselves, and data sets -- no matter their scale -- are still objects of human design. The tools of big-data science, such as the Apache Hadoop software framework, do not immunize us from skews, gaps, and faulty assumptions. Those factors are particularly significant when big data tries to reflect the social world we live in, yet we can often be fooled into thinking that the results are somehow more objective than human opinions. Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.

Lesson Learned: We created the graph below using NodeXL. It shows the 5 key types of participation that visitors can engage in on the ACTion Alexandria website. In this graph, each dot represents a site visitor. Color represents how many activities site visitors have performed (e.g., orange=all 5 activities, dark blue=just 1 activity). Size also indicates the number of activities site visitors have performed. Each line represents an activity the site visitor engaged in on the website. The thickness of the lines (also referred to as edge thickness) shows the number of times a site visitor has performed an activity.

The graph highlights the following things about site participation:

1. Most people only perform one activity, although a significant number perform two activities.
2. Voting is by far the most popular way that people engage with the site.
3. Blog posters post many times, but don’t tend to comment on each other’s blogs.
4. People who engage with multiple types of activities are more likely to engage in them multiple times (i.e., have thicker lines).

More help for nonprofits! https://twitter.com/morriscox/status/329358542844870657

Not sure I agree that it is an output vs outcome ...

Good data scientists = good musicians

example of data philanthropy

More than a million people have now used our Wolfram|Alpha Personal Analytics for Facebook. And as part of our latest update, in addition to collecting some anonymized statistics, we launched a Data Donor program that allows people to contribute detailed data to us for research purposes.

Helps you track the multi-screen experience (for context, this piece from Brian Solis (http://www.briansolis.com/2013/01/from-the-big-screen-to-the-little-screen-the-evolving-relationship-between-tv-and-search/)

Useful flow chart

A transcript of the chat and some analytics (not curated).   I think you need a human touch.