Before #MillionsMarchNYC, a Protest Movement Takes to Facebook and Twitter

December 12 2014 is the day before the Millions March in New York City, an organized reaction to the death of unarmed black men at the hands of the police and more broadly to structural forms of racial discrimination. Tomorrow, a variety of professional journalists will hopefully describe the messages and activities of the protest and reactions to this protest. Today, we can study the run-up to the Millions March by watching people talk about it on Facebook and Twitter.

Facebook, the social media website that most people know best, lets users create personal accounts and pages that they control. Administrators of a page for a group or event can allow posts by others, but they can also purge them if they find the content disagreeable. For announcing activist events, Facebook is a top-down affair. If you want to know what movement organizers think of their protest event, look at their Facebook page. The following is a word cloud taken from administrative posts to the MillionsMarchNYC. Words are larger in this graphic if they occur more frequently:

A Wordle Word Cloud representing the frequency of various words used by organizers of the MillionsMarch in New York City on December 13 2014

We see a lot of practical information here, many references to locations and plans and logistical concerns.  This is what’s on the mind of movement leaders. What’s on the mind of the many thousands who are thinking about going?

Twitter is a social media website unlike Facebook, a website on which certain people own Pages and control those Pages’ content. On Twitter, subjects are organized by hashtags, which no one owns, no one can purge, and which therefore tends to be driven from the bottom up. A corporation with an image problem on Facebook can simply delete comments. Woe betide the corporation that offends on Twitter; it may entirely lose control of the public conversation about itself. If you want to know what people are thinking about a social movement inside and outside its leadership, look at Twitter.

To do just that, I’ve gathered up all Twitter posts (“Tweets”) using the hashtag #MillionsMarchNYC. Perhaps the simplest way of characterizing #MillionsMarchNYC tweets is over time; as of 12 Noon on December 12, here’s the trend in posting volume:

Graph: Volume of Twitter Posts using the hashtag #MillionsMarchNYC through December 12, 12 Noon Eastern Time

5,415 tweets using the newly-created hashtag were posted from November 26 to December 12, but the dates November 26-30 are not even included in this graph because the number of tweets during that initial period — just 6 — is miniscule in comparison to the conversation two weeks later. The trend clearly indicates a spike in use of the #MillionsMarchNYC hashtag, especially over the last few days before the march, but what ideas are associated with the spiking hashtag?

A useful feature of Twitter for answering that question is that a single post may contain more than one hashtag. The co-occurrence of #MillionsMarchNYC with other hashtags in the set of Nov. 30 – Dec. 12 tweets is indicated in the following frequency table:

hashtag frequency
#blacklivesmatter 2020
#icantbreathe 1360
#dec1314 1232
#nyc2palestine 832
#shutitdown 317
#ericgarner 316
#nyc 170
#stolenlives 168
#ferguson 136
#dayofanger 128
#thisstopstoday 116
#mikebrown 103
#justiceleaguenyc 91
#fromtherivertothesea 90
#washingtonsquarepark 72
#indictthesystem 71
#nyc2ferguson 66
#anonymous 62
#wecantbreathe 62
#expectus 61
#nojusticenopeace 55
#intersectionality 49
#palestine 47
#d1314 44
#12/13/14 35
#41986 35
#12/13/2014 35
#freepalestine 27
#millionsmarchsf 25
#akaigurley 22
#weekofoutrage 22
#justiceforericgarner 21
#directaction 19
#justiceformikebrown 19
#alllivesmatter 18
#jailsupport 18
#millionsmarch 17
#handsupdontshoot 16
#equalrights4all 15
#humanrightsday 15
#michaelbrown 15
#opbelgium 14
#santacon 14
#ftp 12
#icantbreath 12
#nycprotest 12
#dayofresistance 11
#dec1213 11
#love 10
#millionsmarchoakland 10
#nojusticenopeacenoracistpolice 10

In the interest of brevity, I’ve only included hashtags used at least ten times in this list.  Just three hashtags co-occur with #MillionsMarchNYC more than 1,000 times: #blacklivesmatter, #icantbreathe and #dec1314.  The tail of the distribution is long, however, with many hashtags occurring a handful of times or just once:

Frequency Distribution of Hashtag CoOccurrence with #MillionsMarchNYC from November 26 to December 12 2014

These many hashtags do not simply co-occur with #MillionsMarchNYC in these Twitter posts, however.  They also sometimes co-occur with one another, forming a co-occurrence network that tells us something about the symbolic landscape of the leadup to this protest.

Sometimes the truth is messy; the following is a graph showing the complete co-occurrence network of hashtags used with #MillionsMarchNYC (the #MillionsMarchNYC hashtag itself is removed from the network to highlight connections between other tags).  Every hashtag is a node in this network and every co-occurrence between two hashtags appears as a tie between the two nodes.  A tie is drawn more darkly if the co-occurrence happens more often, and a node is drawn in greater size if the hashtag it represents co-occurs with a greater number of other hashtags.  Nodes are given different colors to highlight sets of nodes that are more strongly connected with one another:

Complete Co-Occurrent Network of Hashtags in #MillionsMarchNYC Twitter Posts, Nov. 26 to Dec 12

That’s pretty hard to read, isn’t it?  A few tags are evident, but there are so many that they overlap with one another, blending into a blurry mess.  The culture of a social movement can actually be a lot like that, with a large number of voices saying so many things.  But if we start to filter out the least common hashtag utterances, clearer patterns begin to emerge.

Here’s the same Twitter hashtag network, but this time just showing the hashtags for which co-occurrences happen at least 5 times:

Network of Hashtags Co-Occurring at least 5 times in the #millionsmarchnyc network on Twitter, Nov. 26-Dec. 12 2014

Here’s the same Twitter hashtag network, but this time just showing the hashtags that co-occur with some other hashtag at least 20 times:

Network of Hashtags Co-Occurring at Least 20 Times in the #millionsmarchnyc hashtag on Twitter, Nov. 26 - Dec. 12 2014

And here’s the same Twitter hashtag network, but this time just showing the hashtags that co-occur with some other hashtag at least 100 times:

Cultural Network of Hashtag Co-occurrence in the Tweets mentioning #MillionsMarchNYC from November 26 to December 12 2014

If we filter for frequency, we lose detail, but at the same time the core of this movement’s culture becomes apparent.

Although I stand by my claim that this hashtag network indicates something about social movement culture, I should note a few important limitations.  First, the use of a hashtag involves a person deciding how they would like others to categorize their declarations.  These are professions of manifest culture; latent culture remains hidden.  Second, Twitter is not a form of social media that is used by everyone; according to the Pew Internet Project young adults, urbanites and African-Americans are disproportionately likely to post to Twitter.  However, it’s important to note that this is exactly the population that forms the strongest constituency for the Millions March in New York City. In addition, even with the limitations I’ve just noted, the conversation on Twitter is much more expansive and inclusive than the conversation within the movement’s core organizing cadre.  If we’re interested in distinctions between leaders and potential participants in a social movement, Twitter is a pretty good place to look.

Tool Postscript. For data gathering, I used the Twitter API.  For data processing, I used UCINET.  For data visualization, I used NodeXL.

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?