A Map of Popular Connotations for 12 Social Media Sites, Winter 2014

If I say “Facebook is…,” how would you complete the sentence?

The response of any individual person to that question may be idiosyncratic, but when we look at the aggregate patterns that build up across the responses of many people, trends emerge that reflect our cultural beliefs and values regarding social media.  One convenient way to track trends is through Google Autocomplete.  When you enter a term in the Google search bar, have you ever noticed that certain suggestions appear to complete your thought automatically?

Google Autocomplete suggestions in November of 2014 for Facebook Is...

These are not random suggestions.  Rather, they reflect a weighted combination of how often different phrases appear in other Google “users’ searches and content on the web.”  Speaking in sociological terms, they are an indication of the most salient cultural associations with the phrase you’ve started typing.

In the autocompletion of “Facebook is…” that you see above, results are presented as a simple list of items, but it’s possible to obtain richer information than this. First, I’ve nabbed Google’s autocompletion lists for 12 of the most popular English-language social media platforms: Facebook, Twitter, Tumblr, LinkedIn, Vine, Flickr, MySpace, Ello, Instagram, Pinterest, Google+, and YouTube. To each platform’s name I’ve added the prompting word “is” and found up to 10 most-popular search suggestions (Some new platforms like Ello have low enough search volume to generate few results. Some other platforms have repetitive results I’ve combined — “Flickr is slow” and “Flickr is too slow” are just counted as “Flickr is slow.”). An interesting feature of these lists is commonality. Despite the rich variety and nearly endless possibility of the English language, many words to complete the phrase “_______ is…” appear on Google’s top 10 list for more than one social media platform. For instance, the phrase “______ is slow” is among the top 10 results for Facebook, Tumblr, Flickr, Pinterest and YouTube. The phrase “_______ is dead” is among the top 10 results for a full 9 out of the 12 social media platforms studied here.

To graph commonalities, I’ve created the 2-mode semantic network graph you see below. A 2-mode (or “bimodal”) graph is one in which there are two kinds of nodes indicating two different kinds of objects. In this graph, social media platforms are the first kind of node, and they are indicated in yellow. The second kind of node is a top-10 ending of the phrase “________ is” by Google autocomplete. These are color-coded pink if the phrase completions indicate negative sentiment, green if the phrase completions indicate positive sentiment, and white if there is no clear sentiment expressed with the phrase completion. For some ambiguous phrases such as “YouTube is on fire” and “Pinterest is ruining my life,” a quick browse through Google search results helps to make sentiment more clear (both of these phrases turn out to be complimentary). Finally, a line is drawn from a social media platform to a phrase if that phrase is listed in the top 10 Google autocomplete results for that social media platform.

Social Media Is... Most Common Associations of Popular Social Media Sites as Identified through Google Autocomplete

For the 12 social media platforms, there are 68 distinct phrase completions listed in the Google autocomplete top 10. A large majority of these phrase completions communicate clear sentiment, and a large majority of those sentiments are criticisms. Mentions of slow speed, crashes and unavailability appear common. With the exception of YouTube and Pinterest, all of the 12 social media platforms are popularly depicted as “dead” or “dying.” Predictions of doom for social media platforms appear to be a cultural universal, at least among the socially-distinct set of participants in social media and web searches. Facebook, LinkedIn, Vine, Flickr, Ello and Instagram have no positive phrases listed in their autocompletions. A strikingly positive deviation from the negative trend appears for MySpace. This finding is unintuitive, considering how far interest in MySpace has fallen since 2008. Consider the trend in Google search volume for “MySpace” from 2004-2014:

Relative Search Volume for MySpace in Google, via Google Trends, 2004 to 2014

The letters on that graph indicate influential mainstream news articles mentioning MySpace; does the lack of any articles whatsoever since 2010 hint at an explanation? Without newspaper or magazine articles promoting the MySpace network, and with hardly anyone searching for Myspace anymore, who is left but a small group of true believers in the once-great social network? The strongly positive sentiment toward MySpace in its top-10 rankings may be due to positivity in the small set of people who are still paying attention.

What other patterns do you notice in this graph of popular search completions for social media platforms? Do the autocompletions distinguish between different social media platforms, or do they unify?

3 comments

  1. A really interesting piece, James. I am wondering how closely the “is dead” is connected with the phrase as used to describe Hip Hop. Nas’s 2006 album prompted everyone to declare or debate “hip hop is dead.” The debate is multifaceted, including the irony that Hip Hop was/is, in fact, not dead at all…..but, of course, it’s more complicated than this. The use of the phrase for every one of these forms of social media got me thinking about what this phrase may reveal about these social media forms.

    1. Thanks for the feedback!

      The network visualizations that are at Laura Ridenour’s website appear to be ego networks out to a network distance of 2, branching out from just one central ego and not featuring any crosslinks — so I’m not sure how you would apply that strategy to this network. The network here contains crosslinks, which is at once what makes it interesting to me and also what makes for so many overlapping ties. If I put the nodes with overlapping ties toward the outside of the graph, as the examples you link to do, it seems to me that the crosslinks would be longer and more circuitous.

      I suspect you may be thinking of something more clever than what I’m talking about, though — please send me on any visualization you’ve got (e-mail james.m.cook@maine.edu), and thanks again.

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