Thursday, November 14, 2013

Psychology of Sharing on Social Media: Attention, Emotion and reaction

I am very glad to see my Boston Globe/Facebook study well received by curious readers and featured by several organizations, such as the Harvard Nieman Journalism Lab, Chartbeat, Social Fresh, and ISHP Consulting. Meanwhile, I've been giving talks on this research at different places, including the Boston Globe, Mozilla Festival in London, Spiegel Online in Hamburg and Hacks/Hackers Berlin. If you find this research interesting and want to further the discussion, please buzz me on Twitter @sonya2song or drop me a line at sonya2song#gmail. Please also feel free to download the slides (last updated on December 9, 2013) developed for my presentations.

In the previous study, I presented data analysis that examined how users read and share Boston Globe posts on its Facebook Page. In this extended analysis, I’ve included qualitative analysis with a focus on content, cognition and emotion. My goal is to help newsrooms better promote their stories on and attract more attention from social media.

To achieve this goal, I’ve been digging into psychology literature for inspirations. Overjoyed, I’ve discovered some theories and findings that are portable to the social media environment:

  • Two modes of thinking, fast and slow, attract different types of attention.
  • Sharing on social media is
    • Charged with emotions,
    • Bounded by self-image management, and also
    • By concerns over relationship with others.

Again, this report is based on the three key metrics featured by Facebook Insights: reach, engaged users, and talking about this. According to Facebook, reach is defined as “the number of unique people who have seen your post”; engaged users as “the number of unique people who have clicked on your post”; and talking about this as “the number of unique people who have created a story from your Page post. Stories are created when someone likes, comments on or shares your posts; answers a question you posted; or responds to your event”. These metrics are counted as absolute numbers of unique visitors in various ways and reflect user behavior from passive consumption to active interaction.

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In the proto-analysis of Boston Globe traffic on Facebook, I reported the findings on image size and the “BREAKING” label. The general pattern is that illustrating a post with an image is associated with higher traffic compared to no image, so is a large image compared to a thumbnail. This pattern holds across three key metrics by Facebook (Figure 2). In addition, mere “BREAKING” is associated with a higher reach, although not with engagement or talking about this (Figure 1). In fact, not only BREAKING NEWS but also other uppercase words are associated with a higher reach, including WEATHER WATCH, MAJOR UPDATE, BIG PICTURE, NOW LIVE, etc.

As a hardworking journalist, you may tell me it’s upsetting to know that readers are attracted to this kind of superficial stuff like BIG PICTURES and BREAKING NEWS. But the good news for you is that the attention triggered by primitive tricks is fairly cheap. To gain more engaged attention, sophisticated messages would be a better choice, which we’ll discuss in the section on cognitive strain and System 2.

Figure 1: "Breaking" is associated with higher "reach"

Figure 2: Larger images are associated with higher traffic

As a not quite positive example, MIT Technology Review may show us how to gain little attention. Look at its Facebook Page, we can see a lot of big T’s, certainly the logo of the magazine. It’s quite obvious that the stories are shared as links and the logo is automatically extracted by Facebook. As such, these stories have failed to have an interesting or simply relevant visual companion. The repeated T’s may also have turned the fans blind toward this symbol. The sad situation is that, even though the Review generates a lot of thrilling stories, its Facebook presence is far from compelling—you may have noticed the small numbers of shares and likes in Figure 3.

Figure 3: Facebook Page of MIT Technology Review

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