Creating a useful survey that entices your audience to respond, however, requires planning and time. Think about it: If a video does not captivate within 10 to 15 seconds, people click off. That’s for an an activity that requires them to just sit back, relax and watch. Now imagine how difficult it is to get people to lean in, to contemplate and analyze their own experiences and reactions as they fill out a survey.

Here are a few tips for journalists on creating a compelling and effective online survey tailored to return results.

Focus

Before you even begin to write up the questions, you need to ask what exactly you are trying to learn from this survey? Just like a well-written article or well-produced Web video piece, keep it focused. Don’t try to cram in questions to cover all the different angles of your topic. Pick a focus and stick to it. And be sure the results are presented quickly and in a way that will be interesting to respondents

Length or Time

No one wants to sit through questions after questions, scrolling and scrolling down a Web page. Once people realize a survey is going on and on, their focus wavers and they put less thought into their answers. So keep it short and choose your questions wisely. Ask only questions that you know you need answered. Each question should result in a data point that works toward goal–whether it is information on source with a particular experience or it backs or disproves a thesis. Here is an example of a brief, focused survey from Lives in Focus: Family Life Behind Bars

In other words, your survey should require minimum scrolling no more than three to five minutes to fill out completely and thoughtfully. Have a look at this survey on unreported crime. What’s the problem here?

Types of Questions

There are numerous categories of questions–from multiple choice to open-ended–that can return exactly what you need if deployed correctly. This survey, done by The Local, was a smart follow-up to story about a fatal accident in the community. But editors later realized the questions asked were subjective and very hard to quantify and map in a meaningful way. This survey about cultural diets, also done by The Local, was much easier to quantify.

• Multiple Choice:
  • Offer discrete numerical quantities rather than descriptive qualities so that you collect numbers that can be graphed. For example, “How often do you eat out?” Never (0 times); No more than twice a week (1-2 times); Often (3-5 times) / Daily (5-7 times). Avoid: Sometimes; Often; All the time. These are subjective qualities.
  • Make the choices mutually exclusive. In other words, people should not struggle between the choices or have several apply to them.
• Check Lists:
  • Giving people the option of selecting various common items or experiences will make it more likely that people complete the survey.
  • Make sure to give them choice of adding “Other” and a place to enter what “other” is.
• 1 to 5 scale:
  • Allows people to rank their experience, likes and dislikes.
  • Always keep the scales well-balanced. At one end is “Excellent” and at the other end is “Atrocious.”
  • Space your adjectives evenly. In other words, the choices should represent a complete spectrum and not leave gaping holes. For example, you should avoid: “Loved the event / Had a good time / Hated being there!” There are several degrees missing between “Had a good time” and “Hated being there” that could provide useful data.
• Yes and No:
  • As in all forms of journalistic interviews, avoid “Yes” and “No” questions.
  • Caveat: There are some good uses of the Yes/No question in a survey. After you collect some background information or context, you may ask a Yes/No question to categorize each respondent and then lead them into a separate branch of the survey.
• Private Info:
  • Remember to ask for a name and contact info. You’ll need this to verify or follow-up.
  • Inform people that you will NOT be sharing or publicizing the data in any way.
  • Use a Text box to collect this data.
• Open-ended:
  • You provide a longer text box to capture people’s experiences and perceptions.
  • Limit this to one or two MAX per survey. Too many open-ended questions can turn off respondents and limit your ability to chart or graph results because the answers often are not quantitative.
  • An optional, open-ended question or two at the close of a survey can sometimes yield great material to be used as anecdotes  or quotes.

Order of the questions

• Provide a variety of question formats to keep them interested filling out the survey
• Using the same format question after question can result in people answering without much thought.
• Make them flow in a logical order.
• Perhaps one question answers a question generally, while the next asks for specifics.

Presenting the Findings:

• Just collecting the data makes the page appear static. Instead, consider presenting the raw data in real-time as people fill out the survey. Seeing results encourages participation.
• Or entice participation by saying respondents will be taken to results page once the survey is completed.
• Is there an end-date on the survey or will you continue to accept responses. A deadline might encourage participation but it might also be irrelevant.
• Crowdsourcing v. Open-Source: Will you share the data in a format that others can analyze and manipulate?
• Is this a one-way experience. They give, you take? Or can the data provide a service to those who took the survey? Can they use that info to make any informed decision?

Final Touches:

• Keep questions simple. People should have to figure out what you are asking them!
• Make sure you are not passing judgment. You want to find out what your audience thinks. The survey is not your soap-box.
• Have a friend or colleague take the survey:
  • How long did it take them?
  • Were they confused about the any of the questions?
  • Are you missing an important element?
  • Is there a stronger logical order to ask the questions?
  • Were they interested or bored?
• Once you publish it and have some results you can’t change it. So get it right!
• Search Engine Optimized Title: Write a strong SEO headline that draws an audience.
• Compelling Precede: Write a strong intro that entices people to participate.
• Provide a time estimate: “This survey will take no more than 5 minutes to fill out.”
• Remind your audience that this is not a scientific survey based on population sampling.
• Who ever has the link can participate and those who don’t have the technology can’t.

The seven-part video – an hour in total – along with the rich assortment of examples, resources and tutorials is as compelling as it is complete a road map of the way forward.  Journalists ranging from the indie blogger to those working in large corporate outlets need to learn how to present stories extracted from the unprecedented amount of  data now available. That data may be collected independently with free and easy-to-use polling tools like Polldaddy or gathered  through sites like Data.gov and Google Public Data Explorer.

Here are two examples of data visualization presented in the documentary:

The Jobless Rate for People Like You, developed by The New York Times, allows viewers to drill down and personalize unemployment data.

The Stimulus Tracker, by MSNBC.Com, allows viewers to see where stimulus package money has been spent down to the county level and weigh its effectiveness. Viewers can also track where the money was spent relative to the voting records of politicians.

The idea that information presented visually and interactively on the web is a powerful way to draw in readers isn’t all that new. Infographics and interactive illustrations of events ranging from the trajectory of a plane crash to a winning Superbowl play have been around for years.  But growth in data visualization specifically has been hampered by the prohibitive  time and cost of parsing the data, developing the code and producing the final product.

The documentary does an excellent job of addressing these issues and the many other practical realities of producing and presenting visualization in a journalistic context.

In ‘Part IV: A New Era in Infographics’ Hannah Fairfield,  Graphics Director  for the Washington Post,  points out the importance of simplicity and the need to clearly present to viewers how to navigate the visualization. It’s also important to present the information in a way that is meaningful to those represented in the data.

In ‘Part VII: Technologies and Tools’ an assortment of heavy hitters in the field discuss the variety of tools now out there or in development that allow news organizations large and small to reduce the coding involved in producing interactive data visualizations. Many Eyes,  Protovis, and Flare are examples of software that offer templates to present timetables, charts and maps among other things.

In addition to their value as news content data visualizations have a lot of design appeal. IBM researcher Marten Wattenberg acknowledges that while stream graphs like ‘The Ebb and Flow of Movies: Box Office Receipts 1986-2008‘ are beautiful and effectively draw readers in, in reality they may not provide much depth of information. In the news world there is often a trade-off between design, approachability, deadlines and the actual information contained in a graphic.

In ‘Part VI: Exploring Data’ the documentary hones in on a topic that comes up throughout: the need to contextualize data and to give it narrative structure — the need to tell compelling stories with the data. Award-winning New York Times designer Amanda Cox along with others acknowledge the difficulty in striking a balance between allowing users to personalize data and draw their own conclusions while also providing the kind of narrative context that makes the information valuable journalism in the first place.

This may endure as data visualizations most vexing challenge.

I was recently helping some students identify the best day for an event they were planning, and suggested they use some kind of “preferential voting system,” one that allowed users to “rank” their answers, rather than just submitting a single “best” response. The idea was to allow voters to create a list –from most preferred to least preferred — in order to find the group’s “least worst” option.

Why bother? Let me illustrate. Let’s say you and your colleagues want to go to lunch, but can’t decide between Chinese, Italian or Thai. Half the group loves Chinese but hates Italian, the other half loves Italian but hates Chinese, and everyone is just fine with Thai. A standard poll that forced a single response would show a tie between Chinese and Italian, with Thai in third, leaving you as hungry as when you started. On the other hand, a ranking poll would show Thai as the top choice, i.e. the least undesirable option. Spring rolls, anyone?

Now, the only problem with my suggestion was that while I knew I’d encountered a web-based survey tool like this a couple of years ago while visiting MIT Media Lab, I couldn’t remember what it was called or where to find it. And a quick check of other survey-building tools I’d successfully used before didn’t unearth similar functionality, so I was momentarily stuck.

No problem! A quick query to my professional online network on LinkedIn pointed me to that MIT tool within a few hours. Called Selectricity, it was created by MIT Media Lab‘s Computing Culture group as a Knight Foundation-funded Future of Civic Media project. Selectricity has a very easy-to-use “QuickVotes” function that allows you to create polls with amazing speed, and with a nifty sorting tool that has users dragging their preferences around the list before submitting their vote.

But the even nicer thing about my LinkedIn pals is that they also pointed me to a slew of other preferential polling tools and techniques. I haven’t been able to check these all out, but would love to hear about it if you do. Here’s what they suggested:

• Lots of folks pointed out that Google Forms can be used to record responses on a 1-5 scale (Thanks Len De Groot of the Knight Digital Media Center at Berkeley J School, Mathilde Piard of the Palm Beach Post, Dorian Benkoil of Teeming Media, Sree Sreenivasan of Columbia J School and Sandeep Junnarkar of CUNY J School)
• SurveyMonkey offers ranking functionality, emailed Joseph Maser, a senior business analyst and process engineer consultant at Autodesk, who says he’s used it and that it works great (although it may be a feature only available to paid accounts).
• Surveygizmo does allow respondents to rank choices, says former colleague TereLyn Hepple, a web content developer and technical writer at ECi Software Solutions. And it can be free depending on your response rates. Plus, she added, Micropoll does ranking by entering numerals and it’s free too.
• Cvent’s web surveys can do ranking as well, according to Sherrie Mersdorf, a database marketing analyst there. Cvent has a “Rank Order” survey, a vertical list of categories with a numeric text box next to each that respondents rank in numerical order

So a big thank you to all those folks that pointed me to Selectricity (Lisa Williams of Placeblogger.com, Jose Zamora of Knight Foundation, Jody Brannon of News21, Michele McLellan and Chrys Wu), and to the other folks who offered suggestions and responses (Rob Duncan of Biritah Columbia Institute of Technology, Paul Grabowicz of UC Berkeley J School, Joe Filippazzo of CUNY J  School and producer/programmer Wallace Jackson).

If you know of other survey tools, by all means suggest them below. We’ll be adding a page with links on our J School wiki page, which can be updated anytime, and will post it here when it’s live.

Tracking audio changes assume that louder scenes (explosions, musical crescendos, shouting) correspond to higher levels of drama. Rapid visual changes (quick motion across the screen, camera motion, or rapid edits) also correspond to action, a quicker tempo, and higher levels of drama. A combined index of audio and visual changes graphed over the length of the movie represents its unique fingerprint, revealing its dramatic highs and lows.

I analyzed forty noteworthy movies and collected the results in this interactive tool. Use it to explore the dramatic profiles for each movie and their corresponding scenes. Do the highest peaks in each profile match the movie’s climactic moments?

Explore the Story Analysis tool, which was used to produce the graphs. Use it to see how each movie’s audio and visuals are analyzed in real-time. You can analyze your own movies (FLV or MP4 format), output the data, and post the results for others to see.

How it was done
First, all the movies had to be converted to the correct Flash-friendly format. Each movie was converted to an MP4 (H.264 codec) file using Handbrake, a free open-source video transcoder. Then I had each movie stream into Flash with the FLVPlayer component.

Tracking the audio changes

Audio levels were analyzed with the ActionScript command, SoundMixer.computeSpectrum(). The command takes a snapshot of the current sound and stores the information as a series of numbers that can be translated visually. While my sound visualization is rather simple, there are countless creative ways to visualize sound. There have even been contests for the most creative visualizations. Since I was most interested in the variation of sound levels throughout the movie, I captured the amplitude (or volume) of the sound every 10 milliseconds and graphed it with a gray line. An average of the sound amplitude was calculated and graphed with a bold white line.

Tracking the visual changes

Every 10 milliseconds, Flash grabbed the image from the video stream with the BitmapData class. The command, getPixel(), gathered the red, green, and blue color information from each pixel. The red, green, and blue color distribution of an image is known as an RGB histogram. My goal was to track changes between histograms that would indicate major visual changes due to camera motion, edits, or subject motion. Much research has been already done on the subject of tracking shot changes for video cataloging, involving complex (and patented) algorithms. I made my calculation quite simple, determined by differences in the histogram area coupled with a dampening function to normalize the extreme values. The resulting index, which reflects visual changes, was graphed as a gray line. An average of the index was calculated and graphed as a bold white line.

Combining audio and visual changes

Combining the audio and visual indices resulted in what I termed, the “drama index”, a measure of the dramatic highs and lows in a movie. The overall shape of the profile, shown in red, can be interactively smoothed out or made more detailed by changing its resolution in the Story Analysis tool.

What does your favorite movie look like?
Analysis of forty distinguished movies–the top ten of all time, the worst ten, the ten highest grossing films, and the previous ten Best Pictures–not surprisingly reveal no common pattern, but it does provide a standard, objective way of tracking a film’s dramatic peaks and valleys–their position, duration, and intensity. This screenshot is a profile of Star Wars. Note the dramatic beginning when Princess Leia’s vessel is boarded, and the slow build-up to the three dramatic peaks at the end: the rescue from the Death Star, the duel between Darth Vader and Obi-Wan Kenobi, and finally the destruction of the Death Star. The analysis works best on modern action films. There is, of course, no consideration for acting, for cinematography, or for the dramatic climaxes that may come in quieter moments (such as the sudden change that crosses an actor’s face with a revelation).

Other movie visualizations
There are many other interesting visualizations of movies. NetFlix recently ran a contest to see if the public could find a more effective way to predict which movies users would prefer based on past ratings. The results of two of the top teams can be visualized as a network of similarities between movies, or as a landscape with similar movies clustered together. (Based on these maps, if you liked Star Wars, then you probably also liked RoboCop).

One recent visualization cleverly plotted the interactions between characters. The hand-drawn map and synthesis of time and geography reminds me a little of Charles Minard’s map of Napolean’s march to Moscow, as discussed and praised by Edward Tufte as a gem of information design.

Finally, the New York Times produced a fascinating look at the box-office revenues of the movies. I love seeing the periodicity in the graph reflecting the predictable huge bumps during the summer blockbuster months and holiday season before the Oscar considerations. Notice also the relatively short, squatter profiles of recent movies compared to the long tails of movies in the past.

What more can we visualize of movies, or the structure of individual stories?