Tracking the Mood of Americans: Use Twitter if you want to prove they’re happy

July 25, 2010 | 3 Comments

An article in the New York Times this week discussed a research project that is attempting to track the mood of Americans using Twitter as the data source. The project involves researchers from Northeastern University College of Computer and Information Sciences and Harvard Medical School. It is certainly reasonable that a group of scientists can develop algorithms that accurately predict the mood of Americans. However, Twitter data is not simply and instantly predictive of the general population of Americans. Given that only 7% of people who are online even use Twitter, it is risky, and can easily lead to wrong conclusions.

Want to see a real example? No problem.

Let’s look at consumer opinions related to one specific product, the iPad.

  1. First, we gathered thousands of opinions from across the internet, from blogs, microblogs, forums, question and answer sites, personal sites, all of which mentioned the iPad. Sites like YouTube, Blogger, Twitter, and thousands more were included.
  2. Then, we categorized all of the conversations into two groups, 1) everything from Twitter and 2) the entire internet space.
  3. Next, we determined the level of emotion for every online conversation. Specifically, we determined whether the emotion of the conversations was extremely happy, somewhat happy, neutral, somewhat unhappy, or extremely unhappy.
  4. Finally, we created the pretty little charts that you see on the right of this page.

What’s the first thing you notice from these charts?

Not one single chart has two bars that look the same. What is the percentage of tweets that reflect an extremely happy opinion? 15%. What is the comparable number for the entire internet? 5.6%. I hope it’s not just me, but 15% doesn’t look like 5.6%, not even if the 5.6% is averaged up to 6%. There is a big difference in the percentage of people who have extremely happy opinions on Twitter vs the entire Internet.

The same trend is apparent when we look at the percentage of people who are extremely unhappy with the iPad. 11.3% of tweeple are extremely unhappy compared to just 1.9% of the entire internet space. All five of the charts lead to the same conclusions. Twitter results do not equal Internet results.

It’s not 1 to 1

Clearly, the relationship between Twitter data and total internet data is not 1 to 1. It’s impossible to gather Twitter data,  analyze the sentiment, and be confident that it represents a wide, more general audience.

Perhaps people on Twitter have more extreme opinions than everyone else; perhaps they are less likely to guard their remarks so that the more extreme opinions are shared; perhaps Twitter opinions are in fact the closest to the average American opinion. Whatever the reason, it is undeniable that the mood on Twitter is unlike anywhere else.

Prepare to be wrong. Prepare to explain contradictions. Generalize Twitter mood at your own risk.

Links that might interest you:

iPad on EvoPlay
New York Times article
Conversition on Facebook

3 Comments so far
  1. by Jeffrey Henning

    On July 25, 2010 at 2:51 pm

    Great article, and a great point. You put less thought into a 140-character tweet than you do a 140- or 1,400-word blog post: Twitter may be more accurate at capturing instant sentiment rather than considered sentiment.

    By the way, how did you handle retweets? If someone said “I hate my iPad” and it was retweeted a dozen times, would your sample count it once or 12 times?

  2. by Conversition Team

    On July 26, 2010 at 9:35 am


    Handling retweets is a tough topic with different points of view. Do you ignore them as simply being duplicates and not adding any new information? Are unaltered retweets agreement with the original tweet or a way to draw attention to information you disagree with? Do you include them because every person’s opinion counts regardless of how influential, or not, they are? Our stance is to include them. Across thousands and millions of people, the dominant opinion will be obvious.

  3. by Ben

    On August 31, 2010 at 11:05 pm

    Great stuff. I have to say though, I think though that these findings differ from those in the latest edition of Quirks, where twitter was found to be more negative. I guess, in summary, channels will differ.

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