Facebook Friends analysis… So many options!


A Facebook plugin called Find Your Best Friend On FB has blown up this week.

I assume that it looks at private messaging frequency and frequncy of likes and comments and then pops out a photo of you with that person.

I don’t really like these apps because they’re scanning your private messages and that makes me nervous. I did install it, run it, and then remove it though. It did seem to be accurate.

But there are a ton of other fun ways to visualize and analyze your Facebook network.

The first one is from Wolfram Alpha which has a plug in that does a lot of analysis and visualization, although no “best friends.”

Instead it has social insiders (shares the most friends) and social connectors (bridges between groups (like my twin sister is a bridge between my family group and my schoolmates group).

You can also see what friends like your stuff the most and comments on your stuff the most. That was really interesting to me.

NameGenWeb is my favorite app for this but it is down right now.

TouchGraph is pretty good too and is fast and mostly focuses on the networks that people have put themselves in (usually university networks). It ranks your friends (on number of friends in common). This wasn’t very accurate for me because it looks at those university networks more strongly than other factors. So, for example, a lot of people I grew up with attended Michigan State University in the late 1990s. I also have a number of friends who I did not grow up with who went there for their PhDs in the mid-late 2000s. That doesn’t mean much in terms of the connections between these groups.

FriendsGraph is an interesting one but the visualizations are pretty boring.


I like to use NodeXL and its Social Media Importer, but using it requires you to download some programs, so this is not a quick click. But the analysis is much more detailed (I added the labels to this picture).




#putinout hashtag analysis

civilnet (Via Civilnet.am)

There is a series of protests in Armenia right now, focused on Vladimir Putin’s visit, but overall critiquing Armenia’s possibly joining the Eurasian Union.

Unzipped does a nice summary here.

Here’s my Dec 3 hashtag analysis that is the following relationships. It is basically Armenians (far left), foreigners (middle), and Russians (right).


You can see that pretty much everyone in Armenia that is on Twitter follows each other. :)

This is the Dec 3 reply analysis of the hashtag – much clearer about small communication networks.



Here is Dec 4 reply analysis.


Shenanagins again and again

I’ve written a lot about “winning” hashtags and how this is a boastful tool for organizations. Here’s what I wrote yesterday on it.

I’ve also written about trickery using Twitter. Here’s a good one.

But now I have a new story…

As I was going through the Azerbaijani election hashtags, I noticed something funny.


This is all the users that used the hashtag #azvote13 in the last day. Look at how many people opened a Twitter account on a few days in February of 2013.

So I went to look at what was going on in those days in February. Not only were those accounts made on the same day, but they were made within minutes of each other. (If they’re highlighted the same color, it was the same day.)



So it is possible that there was some sort of training where a bunch of people created Twitter accounts at the same time, so I looked more closely at these accounts made in these days in February.

They generally follow the same few people. They generally don’t tweet a lot. Most haven’t tweeted a lot until this election period. I did a search on Facebook for some of them and no Facebook profile came up for them. It is possible that these young people spell their name differently on Twitter and Facebook – but in general I find that most young Azerbaijanis pick one way to spell their names on social media and stick with it.

So what were they tweeting about on the #azvote13 hashtag?


The same thing. The red/pink tweets are duplicates and the orange highlight is the same time. And they are at the exact same minute.

While it is theoretically possible for tweets to happen at the same minute, 100 tweets at the same minute by accounts all made in the same few days within minutes of each other? That’s a stretch.

What is interesting about this:

- this is way less detectible than buying fake Twitter accounts because the names are Azerbaijani, the profile pictures look like Azerbaijani people, even though there isn’t a lot of evidence that they are real.
- it is entirely possible that these are real people, but regardless, I speculate that one person has all the passwords and probably uses a particular app to send out the tweets at the same time.
- UPDATE 10PM BAKU TIME: I did a quick reverse image search on some of the profile photos of some of the profiles. The photos are ones that people can download and use all over the place. Here are some links and PDFs 1 2 3. And here are the original profiles.
- so, nice try – this was certainly more sophisticated than prior attempts, but still a FAIL.

As always, I’m happy to share these Excel files for people to look themselves.

We are young, heartache to heartache we stand; No promises, no demands #azvote13

Hashtags are an interesting 21st century phenomenon. Hashtags are keywords to organize information to describe a tweet and aid in searching (Small, 2011). Hashtags also take on a symbolic quality and perhaps are an example of metacommunication. When I post a picture of parents recording every minute of a kids’ holiday concert, complaining about how this is ruining the experience, I can add a hashtag #guilty to metacommunicate that I too participate in this. Symbolic use of hashtags also could be a way to show solidarity with some larger Internet community. When one sees a hashtag on a written sign at a rally, it shows some sort of connection to others that recognize the hashtag.

With that being said, analysis of a hashtag is much easier when there is a time-bound event like a rally or a protest, or in the case of this analysis, an election. When a hashtag is proposed for an event or topic, the intention is for a community of users to share information with each other. But hashtags also serve other purposes during an event: they can promote the event itself (come to the protest! #protest); they can give locationally situated information (the police are at the west gate #protest), and allow for live reporting that may send the message out to sympathetic others or media (Earl, McKee Hurwitz, Mejia Mesinas, Tolan, & Arlotti, 2013; Penney & Dadas, 2013).

For an election event in particular, a hashtag can serve as a means to share information, live report, and also to report possible fraud or violations. In the lead up to an election, a hashtag can be used for information dissemination.

With all that being said, hashtags also serve a boastful purpose. When a hashtag “trends” – it is noted by Twitter as being popular at a particular time. Users want a hashtag to trend to gain visibility and attention (Recuero & Araujo, 2012). While occasionally hashtags trend organically, it is much more common that hashtags are artificially pushed to the trending list (Recuero & Araujo, 2012).

This quantification of social media viability is very attractive. It allows a group to “prove” that it has a lot of support, even if it is artificial.

So, with that being said, let’s have a look at the hashtags for the 2013 Azerbaijani presidential election. (Here’s a pre-election report to give you a sense of the background).

A few different hashtags have emerged in the run up to the election. #azvote13 as well as #azvote2013, #secki2013, #sechki2013, and #besdir (the slogan of the main opposition candidate) are some of the most popular. I’ve been archiving #azvote13 and #secki2013 and #besdir for over a month.

It is important to note that pro-governmental forces have been engaging in some serious hashtag shenanigans all this year – hijacking hashtags thus rendering them useless for organizational purposes, amongst other things. However, in the past month or two, opposition youth have gotten more active on Twitter and seemed to take a stronger hold at different points recently. (Stronger hold = were the largest users of the hashtag.) There were a few alternative hashtags that emerged to make fun of a candidate, but overall the type of behavior that was seen earlier this year seems to have calmed down.

All this hashtag battling seems a little silly to me. But as noted before, hashtags are not just about being an information source, but about sending a signal. Thus, that tagging (to one’s own followers) is showing that “I’m talking about the election.”

Here’s some guidance on understanding these charts. One way to understand who a cluster is is to look at the links that they most frequently share and the source of those links. Are they tweeting from state news sources or opposition news sources, for example?

Here are the hashtags tracked over a long period of time:

#secki2013 – for the last month or so

The largest group of users of this hashtag were not connected to other people. But the second largest group was centered around opposition-leaning Hebib Muntezir (who has long been an information source for Azerbaijani news, lives outside of Azerbaijan, and currently works for an opposition-leaning sat/internet TV channel). Muntenzir’s following is quite interesting – the people around him aren’t heavily linked with each other. And they are receiving information from him, not vice versa – implying that he is an information source rather than a back-and-forth chatter.

Group 3 is the next largest group and it is the pro-government youth. They’re fairly interwoven with each other, and it centers on Rauf Mardiyev, the chairman of IRELI. You can see that his followers, like Muntenzir’s are a little distant from him. He is more a source of information than a chatter.

Group 4 is a very tight cluster – this is all the oppositionists. This is the first time that I’ve seen them all together in a cluster like this. Usually they subdivide into smaller clusters, but with links between them. There is a lot of communication between these people and a lot of efficient information sharing.

Group 5 contains the most active Twitter chatters of the opposition youth. They ended up in their own cluster probably because of how frequently they talk with each other.

#azvote13 – for the last month or so

The largest group here is the pro-government youth organization in Group 1. They’re pretty tight, although you can see some distant subclusters.

Group 2 is all the foreign media and NGOs that was covering the election as well as Azerbaijanis and foreigners that “affiliate” with these organizations.

Group 3 are the non-networked people.

Group 4 are the oppositionists and some media (usually when an opposition leader wrote a piece for a particular news organization and the tweet went out “@soandso’s article at @mediaorg”).

Group 5 is opposition youth – note the ties between group 4 and group 5.

Group 6 is muntenzir’s followers.

So what about election day itself?

#azvote13 for just election day

What’s interesting about election day itself isn’t so much the clusters as the content of what was tweeted – Lots of news coverage from every side. Also many instagram and Facebook photos of people voting, their ballots, and occasionally election violations.

So overall, Twitter is a battlefield. What is to be “won” is still not clear to me. I doubt this is a good use of anyone’s time to battle like this, but…

5pm Oct 9 hashtag update

More to come, but…

#azvote13 for last 48 hours

Group 1, the largest group, was unnetworked people.
Group 2 is a big cluster of foreign organizations and some individuals, Azerbaijani and foreign, associated with them. Seems like it was a lot of discussion and re-tweeting of Rebecca Vincent.
Group 3 is pro-government.
Group 4 is Azerbaijanis associated with the opposition.

#secki2013 for last 48 hours

#besdir for last 48 hours

#azvote2013 last 10,000 tweets

Hashtags day before election

#azvote13 mid-September – October 8

Interesting changes here. Group 1, the pro-government forces, are a really tight cluster now. They used to be much less close. Seems like they’re talking to each other more now.
Group 3 is a VERY tight cluster of oppositionists. Strong ties exist between Group 3 and Group 4, centered around muntezir. Group 5 is foreigners and Azerbaijanis that hang out with foreigners.

#azvote13 October 2 – October 8

#azvote13 October 7 – October 8

#secki2013 October 2 – October 8

This is much less contentious than #azvote13.

#secki2013 October 7 – October 8

Election week hashtag analyses

I’ll be continuing to monitor the hashtags, but here is where we stand on Monday morning before the Wednesday election:

#secki2013 for the weekend – pretty dead, but probably will pick up in the coming days
full analysis

#secki2013 for the past 10 days
full analysis

Opposition blogger muntezir is the most powerful tweeter in the network, but groups 3 and 4 are pro-government forces and are really loud on this hashtag.

#azvote13 for the weekend
full analysis

In this hashtag, the pro-government forces (group 2) are “winning” – being louder than the opposition forces. Although muntezir in group 4 and group 3 being a lot of oppositionists and their foreign friends are still holding strong.

#azvote13 since mid-September
full analysis

This tells a great story – while the pro-government forces (group 1) are very loud on this hashtag, all the other big clusters are very well connected and spreading information widely.

Ten thousand signatures felt like ten thousand hands, they carry me

An online petition has been recently been circulating through Azerbaijani Internet circles asking people to support freeing youth activists who have been arrested in 2013, in light of the October 2013 presidential election.

As of early August, 2000 people have signed. (The hashtag suggests they need 10,000 signatures.)

I’m pretty meh about online petitions, although I have recently changed my tuned, as they do provide evidence for “citizen support” in Azerbaijan where public opinion is difficult to ascertain.

Regardless, I’ve done a hashtag analysis of the efforts on Twitter.

Only July 31 when the campaign began, this was the hashtag map.


Popular Azerbaijani Internet personalities Habib Muntezir and Bakhtiyar Hajiyev each have their own clusters of followers and retweeters. The youth organization N!DA (from whom many of the detained activists come) and its leadership make up the largest cluster though.

I did another analysis on August 5 and things look a little different.


Now those key users (Muntezir, Hajiyev, and the official Twitter account of N!DA) from the first analysis are all in cluster 1 together. Cluster 2 includes the leadership of N!DA, separate from the official N!DA account. My guess is that those individuals associated with N!DA are communicating with each other, perhaps about other things, more frequently than they are with the rest of the network, so they have become clustered together.

I don’t entirely understand clusters 3 and 4. Cluster 3 includes some foreigners who tweet about Azerbaijan (including myself). Suggestions on this are welcome.

In my estimation, a lot more of the discussion of this issues takes place on Facebook rather than Twitter. However, analysis of Facebook hashtags is slow in coming.