TweetReach Blog

This post by Union Metrics Co-Founder Jenn Deering Davis originally appeared on the KISSmetrics Blog on April 24, 2012

If you’re using social media, you should be measuring it. But don’t measure just for the sake of having metrics. Instead, measure your social activities so that you can learn what’s successful, what isn’t, and how you can improve.

In this post we will help you get started with social media measurement for your organization by addressing these questions:

• How do you know if your social media activities are effective?
• How do you decide what metrics you should be monitoring?
• How do you calculate those metrics?
• How do you interpret the numbers once you have them?

The Two Types of Social Media Measurement

The two types of social media measurement are:

1. Ongoing Analytics – Ongoing monitoring that tracks activity over time
2. Campaign-Focused Metrics – Campaign or event analytics with a clear beginning and end

Ongoing analytics are necessary for keeping up with the overall pulse of general conversation about your brand and company. Once your brand tracking is set up, you can just let it run and check in regularly to see how everything is going.

Campaign-focused metrics, on the other hand, help you understand the impact of targeted marketing initiatives and will vary from campaign to campaign, depending on your goals for each. An effective social media measurement program will likely include both ongoing and campaign-specific measurement.

Let’s Start With An Example

Let’s say you work at a large consumer products company and are about to launch a new diaper brand. To accompany the big advertising and marketing push, you want to sponsor a one-hour Twitter party where parents and caregivers can discuss raising children, focused on issues around diapering and potty training.

You’ve picked out a unique hashtag, contracted with an influential Twitterer who will pose questions and lead the conversation. You’re ready to go. But now you need to make sure you’re measuring this conversation so you can learn – and later tell your boss – how effective the chat was.

Step 1: Determine Your Social Goals

Before you jump into measuring every single tweet, photo and Facebook comment posted about your brand, first think about your goals with social media. What are you trying to accomplish or gain through these social channels? And which channels are most relevant to those goals?

The first step in your measurement plan should be to generate a list of what you’re trying to achieve from your social media efforts. Social media can serve a variety of purposes, from broadcasting news and information, to answering customer questions and engaging with a community. What is your company trying to accomplish?

You’ve probably already started interacting on social media sites like Facebook, Twitter, Tumblr, Pinterest, YouTube, and Instagram, depending on the type of information and the format of the content you’re sharing. You’ve probably also considered the audience you want to reach and the tools they’re using. So the next step is to think about what you want your audience to do with your content on these channels. Are you trying to get them to read, share, reply, click, purchase, engage? List out all your business goals for social media.

For our Twitter chat example, our goals are probably two-fold:

1. First, we want to spread awareness of the new product to potential customers
2. Second, we want to get to know the parenting community on Twitter, particularly the influencers in that community

Step 2: Create Metrics To Measure These Goals

The next step is to match your goals to actual metrics and behaviors you can measure. For example, if you’re trying to measure engagement, then what is the practical form of engagement you want to track? Is it retweets or reposts? Replies or comments? Clicks? Here are a few suggestions of behaviors to measure, based on a few common social media goals…

• If you want to measure awareness, then use metrics like volume, reach, exposure, and amplification. How far is your message spreading?
• If you want to measure engagement, then look for metrics around retweets, comments, replies, and participants. How many people are participating, how often are they participating, and in what forms are they participating?
• If your goal is to drive traffic to your website, then track URL shares, clicks and conversions. Are people moving through social media to your external site and what do they do once they’re on your site?
• If your goal is to find advocates and fans, then track contributors and influence. Who is participating and what kind of impact do they have?
• If your goal is to increase your brand’s share of voice, then track your volume relative to your closest competitors. How much of the overall conversation around your industry or product category is about your brand?

For our hypothetical Twitter chat, our first goal is awareness, so we want to measure:

1. The tweet volume and reach of our Twitter chat
2. How many unique people tweeted with our hashtag

We’re also interesting in getting to know this community, so we want to know more about the participants, including:

3. Any influence metrics we can find (like follower counts and Klout scores)
4. Relevant demographic information about them (gender, location, etc…)

Step 3: Measure

After you’ve listed the metrics you want to focus on, now you need to find tools that actually capture these metrics, and then start measuring. In some cases, social media channels themselves provide some form of analytics, in some cases you will need to use third party tools, and in some cases you can build your own using APIs.

If you’re not sure which tools to use for which channels, ask around or do a quick Google search and you’ll find tons of options. SocDir is a useful and comprehensive source with a list of more than 300 social media metrics tools.

Many social analytics tools work in real-time, so if you can plan ahead and set up tracking before your campaign begins (and well before your report is due), it will be much easier to access the data you need later.

On Twitter, for example, accessing tweets that are more than a few days old is very expensive, difficult, and far less reliable than collecting and archiving them in real time. When possible, set up your measurement tools before your campaign begins.

The measurement part of this may take some time, so let the tools do their work. Make sure they’re tracking the social posts you’re interested in, do what you can to filter out spam, and then come back in a few days for steps 4 and 5.

Step 4: Monitor And Report

The fourth step is to report your results. Use your initial findings to set a baseline or benchmark for future measurement, and share these early figures with your important stakeholders. Two important questions to nail down are:

• How do your numbers compare to what you expected?
• How do they compare to your competitors’ or related products and campaigns?

One of the great parts of social media analytics is that you can easily run reports about your competitors to see how they’re doing.

This is a also a good time to consider your schedule for regular reporting. Depending on your (and your organization’s) schedule, monthly or quarterly reporting may work best, but weekly reporting may work well for others. No matter the schedule, make sure you’re checking in regularly on your metrics. Don’t let your effort up to this point go to waste! And let your metrics accumulate over time; you’ll see how valuable this data will become after a few months have passed and you have older data to compare to your new data.

In your reports, be sure you highlight the important numbers:

• Include benchmarks or other contextual information so that your stakeholders can quickly understand what all the figures mean
• Consider including visualizations of your data; graphs can help communicate your results quickly and clearly to your audience
• Keep your graphs simple and clean

If you’re interested in reading more about data visualization, I highly recommend the work of Stephen Few; he has some excellent tips and examples.

Going back to our Twitter chat example, we’ll want to prepare a brief report to share internally. We don’t have baseline metrics yet to compare these to, but we probably started with a general idea of what we wanted to achieve with the chat.

As you recall, our goals were increasing awareness of the new product and getting to know community influencers for future interactions. Let’s say our chat generated 750 tweets from 200 unique contributors and a reach of 500,000. Several participants had Klout scores over 60 and tweeted multiple times.

So, even though this was our first chat, these are very respectable initial numbers. Half a million Twitter accounts were exposed to tweets with our hashtag, and we now have a list of 200 people who were talking about diapers, some of them very influential. We can build on this foundation in future initiatives, nurture relationships with these participants and continue to increase awareness of our new product.

Step 5: Adjust And Repeat

The final step is to carefully review your measurement program. How are these metrics doing? Are you missing anything? Was anything superfluous or unnecessary? Figure out what you can improve, make changes, and then measure some more. Check back in with the goals you set initially and make sure your new metrics actually help you address those goals.

In the case of our Twitter chat, we now realize that we also want to measure engagement around our chat hashtag. We’ve decided it’s important to know how many of our host’s tweets were retweeted and replied to, so we can understand what participants found most interesting. We can add this in and include it in our reporting next time.

If you’re participating in social media, you really need to understand how you’re doing. Is your content having the impact you want? Are you meeting your company’s goals with social media? This is why monitoring and measuring your social media activities is so crucial – you need reliable and consistent analytics that help you track your success on channels like Twitter, Facebook, and YouTube.

This post by Union Metrics Co-Founder Jenn Deering Davis originally appeared on the KISSmetrics Blog on April 2, 2012.

So your company is now officially participating in social media. You’ve set up a Twitter account, a Facebook page, even a few Pinterest boards. You respond to customer questions, follow fans, post important news, and thank your advocates for their support.

Beyond that, what are you doing to track and monitor these social interactions? If you’re engaging in social media, then you should be measuring those activities. How else will you know how you’re doing? The good news is it’s easier than you think to measure your social media efforts.

Here are five simple, but oh-so-useful social media metrics you should be measuring right now.

1. Volume

The first – and easiest – social media metric to measure is volume. What is the size of the conversation about your brand or your campaign? Volume is a great initial indicator of interest. People tend to talk about things they either love or hate, but they rarely talk about things they simply don’t care about at all.

While volume can seem like a simple counting metric, there’s more to it than just counting tweets and wall posts. It’s important to measure the number of messages about your brand, as well as the number of people talking about your brand, and track how both of those numbers change over time. For example, Facebook Insights has a useful metric (cleverly called “people talking about this”) that measures how many unique people have posted something to their walls about your brand page.

Learn when volume is higher – are there days or times when more people seem to be talking about your brand? You can use this information to focus more of your own posts during these times to get more engagement, which we’ll talk about in a minute.

2. Reach

Reach measures the spread of a social media conversation. On its own, reach can help you understand the context for your content. How far is your content disseminating and how big is the audience for your message? Reach is a measure of potential audience size.

And of course, a large audience is good, but reach alone does not tell you everything. Reach becomes very powerful when compared to other engagement metrics. Use reach as the denominator in your social media measurement equations.

Pick important action or engagement numbers like clicks, retweets, or replies (more on this in a second) and divide them by reach to calculate an engagement percentage. Of the possible audience for your campaign, how many people participated? Reach helps contextualize other engagement metrics.

3. Engagement

Speaking of engagement metrics, this is one of the most important areas to measure in social media. How are people participating in the conversation about your brand? What are they doing to spread your content and engage with the topic?

In most social media settings, content can be both shared and replied to. Twitter retweets (RTs) and Facebook shares and posts are helpful to know who is spreading your content, while comments, replies and likes are helpful to see who is replying to your content. Think carefully about your goals with social media. Are you focused more on generating interaction (replies, comments) or on spreading a message (retweets and posts)? Be sure you’re using metrics that reflect what’s important to your brand right now.

And are there types of content that generate engagement? Start paying attention to what messages generate the most replies and RTs. It might surprise you what people interact with; it’s not always what you expect.

4. Influence

Who is talking about your brand and what kind of impact do they have? Influence is probably the most controversial social media metric; there are myriad tools that measure social influence, and they all do it in different ways. But one thing they all agree on is that audience size does not necessarily relate to influence. Just because someone has a lot of friends or followers, that does not mean they can encourage those followers to actually do anything.

Based on past actions, we can make assumptions about how influential someone might be in the future. This type of potential influence is useful to decide who to reach out to when you’re preparing for a campaign. Tools like Klout and PeerIndex assign people an influence score. Tools like these measure online social capital and the (potential) ability to influence others.

Kinetic influence, on the other hand, will help you understand who is participating in and driving conversation about your brand and your campaigns, and who gets others to participate in these specific conversations. You can find your brand advocates by focusing on people whose messages are amplified by others, and not just who has the most followers.

5. Share of Voice

Finally, to really understand how well you’re doing on social media, you should consider a share of voice metric. How does the conversation about your brand compare to conversations about your competitors? Determine what percentage of the overall conversation about your industry is focused on your brand compared to your main competitors. And learn from your competitors’ successes; since so many of these social media conversations are public, you can measure your competitors’ impact just as easily as you can measure your own.

Consistency and preparation are essential to effective social media measurement. Pick your favorite metrics and start tracking them now. Use the same formulas and tools to calculate these numbers every week or month. Track your numbers over time and pay attention to how they change. If you see anything that looks higher or lower than what you typically expect, investigate it. By measuring – and paying attention to – these five social media metrics, you’ll be able to better understand the impact and effectiveness of your social media activity.

When the 2012 United States Republican presidential primaries and caucuses began back in January, we took a look at whether Twitter activity could be used as a predictor of the elections. We started tracking all tweets that mentioned any of a candidate’s Twitter accounts (personal and campaign) and based on the Twitter activity coming out of the Iowa caucuses, we saw that Twitter activity was less an indicator of the outcome, and more a reflection of the overall conversation happening around the candidate. Reach, exposure, and activity were largely driven by mentions by popular news and media accounts, many of which have significant numbers of followers and retweets.

Since January, the Twitter activity on the candidates has been staggering – some of the largest reach and exposure we’ve ever tracked, with over 8 million tweets from hundreds of thousands of contributors. These contributors reached more than 120 million unique Twitter accounts and generated almost 22 billion impressions.

Right before the Super Tuesday primaries in March, we launched the TweetReach Republican Primary Tracker which looked at the relationship between what people say on Twitter and what they do at the polls.  In the visualization, we mapped the number of unique Twitter users talking about a candidate to the y-axis, polling results to the x-axis, and tweet volume to the circle radius.

While, based on our previous analysis, we did not believe Twitter conversations could predict winners, we thought it would be interesting to see what tweets can tell us about how potential voters feel about the candidates. The visualizer confirmed that despite a candidate’s tweet volume, reach, and exposure on Twitter, these data were not a good predictor of election results. They are, however, a great way to understand how popular dialogue about a candidate translates into Twitter conversation.

Today, with Rick Santorum bowing out of the race, we took another look and found that Twitter conversation about Santorum had been relatively quiet since Super Tuesday but, as expected, spiked with today’s news as people came out of the woodwork to Tweet about the candidate.

In fact, a full 21% of Rick Santorum’s exposure since Super Tuesday (over 368 million impressions) occurred today after the announcement. When viewed with the TweetReach Republican Primary Tracker, the impact of the conversation around Santorum’s departure is even more pronounced.

We look forward to tracking the upcoming full election. In the meantime, we’d love to know what you think!

This weekend, we tracked tweets about the 47th Annual Academy of Country Music Awards. During the three-hour broadcast on Sunday, April 1, 2012, we tracked 214,407 tweets from more than 96K contributors that reached more than 43.5 million unique Twitter accounts. Tweet volume peaked at 3,686 tweets per minute during the show.

The most retweeted tweet of the night was from @Country_Words and received 1,397 retweets.

The most buzzed about Twitter moments from the ACM Awards show were:

1. Song of the Year goes to Eli Young Band for “Crazy Girl”
2. Entertainer of the Year goes to Taylor Swift
3. Album of the Year goes to Miranda Lambert for “Four the Record”
4. Vocal Group of the Year goes to Lady Antebellum
5. Male Vocalist of the Year goes to Blake Shelton
6. Single Record of the Year goes to Jason Aldean and Kelly Clarkson for ”Don’t You Wanna Stay”
7. New Artist of the Year goes to Scotty McCreery
8. Female Vocalist of the Year goes to Miranda Lambert

Overall, thousands of tweets were posted about Blake Shelton, Miranda Lambert, Taylor Swift, and Reba McEntire. Shelton and McEntire were the show’s hosts, while Lambert and Swift were two of the night’s big winners. Finally, here’s the infographic we prepared for the 2012 ACMs (click to see full size).

What did you think? Did you watch? What was your favorite moment from the awards show?

We’re happy to announce a new TweetReach Pro plan level for our larger enterprise, agency and media customers – TweetReach Pro Ultimate! This plan level is perfect for anyone managing multiple products, clients or accounts.

Our most comprehensive and personalized plan level, TweetReach Pro Ultimate comes with:

• 50 Trackers
• Access to TweetReach Back, our 30-day complete historical archive
• A dedicated account manager to help you get exactly the data you need
• Unlimited snapshot reports
• Unlimited users and projects
• API access

With 50 Trackers in your account, Ultimate subscribers will be able to monitor tweets about all of your campaigns, clients, products and events, in real time. Each Tracker can monitor unlimited tweets about your topic, including up to 20 distinct search queries to be sure we’re finding all relevant tweets.

TweetReach Back is our new historical analytics option. If you missed an important event or weren’t able to set up a Tracker before campaign tweets went out, we can go back up to 30 days and analyze all tweets about your topic. This is a more comprehensive option than our simple snapshot report, with no tweet limits and in-depth metrics like you see in a Tracker. Ultimate subscribers have access to up to 24 hours of TweetReachBack analysis each month.

A dedicated account manager will be available to answer all of your questions, from setting up tweet tracking, to interpreting metrics, to helping you improve next time.

The TweetReach Pro Ultimate plan is $2,500 per month. You can subscribe to the Ultimate plan here, and if you have any questions at all, please let us know.

We recently began rolling out a new look – and some new metrics – in our snapshot reports. As of today, all snapshot reports are now in the new format. Isn’t it so much nicer?

There’s more information about the new snapshot report below, including a few frequently asked questions and explanation about the metrics and our calculations. Or, skip all that and run a new and improved report right now!

How much does the new report cost?

As always, the quick snapshot report (up to 50 tweets) is free. The full snapshot report (up to 1500 tweets from the past week) is $20. The price has not changed.

How is the new report different from the old report?

First, it looks different. Way different and way better. Second, we’ve added some new metrics (details on those below). We’ve moved a few things around, but we haven’t removed anything from the old version of the snapshot report. The new version is just smarter and prettier than ever before.

What new metrics are included in the new report?

There are three major new sections in the new version of the TweetReach snapshot report. They are the Activity, Top Contributors and Top Tweets sections, explained below. There’s a more detailed explanation of all the report metrics here.

• Activity provides details about the tweets in this report, including a graphical timeline of when tweets were posted (times shown in UTC).
• Top Contributors shows you the top three contributors – participants whose tweets appear in this report. You’ll see the highest contributor for each of three influence dimensions: highest exposure, most retweeted, and most mentioned.
• Top Tweets shows the three most retweeted tweets in this report, showing retweet counts for each tweet.

Can I still see the old version of the report?

Yes, you can still access the old version. There’s a View Old Version link in the top right corner of the report.

So, how do I get one of these new reports?

Just go to TweetReach.com and give it a try. Run a new TweetReach report for free right now!

We’re excited to announce a new feature for TweetReach Pro subscribers – projects! Projects enable account holders to selectively share Trackers with their clients and colleagues, support multiple campaigns with one Pro subscription, and easily manage multiple users’ access.

You can use projects to:

• Group related Trackers and snapshot reports together
• Share select Trackers with clients or colleagues
• Manage user access and permissions
• Create guest access for one or more Trackers

There’s more detailed information about how to set up our new projects feature on our helpdesk. Projects are available in all TweetReach Pro plan levels.

Here in the United States, we’re right in the middle of the Republican primaries as the country tries to decide who the GOP nominee for President will be in our election later this year. One of the more interesting conversations around the 2012 Presidential election is the relationship between what people say on Twitter and what they do at the polls. Can we use Twitter conversations to predict election winners? Or, if they can’t predict results, what can tweets tell us about how potential voters feel about the candidates?

With Super Tuesday approaching and the GOP candidate field still wide open, we’ve been tracking tweets about the six top candidates for the Republican Presidential nomination since January 1 – Newt Gingrich, Jon Huntsman, Ron Paul, Rick Perry, Mitt Romney, and Rick Santorum. From those tweets, we built an interactive visualization of how Twitter talks about the GOP candidates, and how that relates to poll numbers over time.

Check out our interactive Republican primary Twitter tracker here or click on the screenshot below.

To create this visualization, we’re using a set of TweetReach Pro Trackers to track Twitter conversation about each of the candidates, along with our API to update the visualization daily. In the visualization, we’ve mapped the number of unique Twitter users talking about a candidate to the y-axis, polling results to the x-axis, and tweet volume to the circle radius. Polling data is from RealClearPolitics.

This post is by Jerry Chen, our Lead Engineer. Look for more in-depth technical posts like these in our TweetReach Tech category.

Here at TweetReach we love data. But what we love more is making data understandable, useful and maybe even a little bit fun. When we saw all the amazing visualizations people have done with the d3.js library, we were inspired to do something with the millions of tweets that flow through our system every day. Fortunately, this amazing data-driven JavaScript framework does most of the heavy lifting and fluently speaks SVG and CSS. As a proof of concept, we put something together for the Grammys. It was a good first step, but we knew we could do much better for the Oscars.

And of course, we did! Check out the TweetReach Academy Awards Explorer.

On the other end of the stack, we were revisiting Apache Cassandra. Since last we took a look at the datastore, it graduated from Incubator, got counters, hit a 1.0 version milestone, and continued to capture the hearts (and columns) of millions. We knew our chart data would be broken down by a time component, so this project would be a great fit for Cassandra.

After a few sketches about what to show and how to show it, we decided to capture tweets containing any mention of the Oscars, and then break them down by a few categories and nominees. For each minute we would measure the volume about a particular nominee, and provide a slider so the user could view the exact volume at a particular minute in time.

The Starting Point

But first, how is datta formed?

From the beginning

Our journey begins, as with many things on the Internet, with text. We wrote Flamingo to consume the Twitter Streaming API (and later on, Gnip PowerTrack). Incoming tweets get appended to an event log, and optionally resque jobs are scheduled based on subscriptions. Normally, we use the latter for our larger pipeline (which includes search, OLAP, contributor and reach calculations), but for this special project we fork the events log and stream it to a separate server.

For moving log files around, there’s Apache Flume, Facebook Scribe, and maybe even time-tested syslog (here’s a great post by Urban Airship), but in the spirit of getting the job done, we can get away with tailing over SSH (and maybe wrapping that in a screen session):

    nibbler$ tail -F /var/log/flamingod/events.log \
             | pv -l \
             | ssh -C parabox 'cat - >> /var/log/events.log'

(We use the capital -F flag for tail so to follow symlinks even if their destination changes, and pv is a great utility which will be explained shortly.) Meanwhile, on the destination server, we employ tail again and stream the events log into a ruby script which reads from STDIN, for the actual data insertion into Cassandra.

The schema is simple. For each tweet, we see if there are any matching terms. If there are matching terms, we extract the timestamp of the tweet, get it into its minute-resolution “time bucket” format (YYYYMMDDHHmm) and insert it into Cassandra. The schema ends up like this:

Optionally, we keep the available time buckets in a special super column called “index.” This is preferable to trying to list all the super columns under the row key. Thus, using the Ruby cassandra gem, an insertion looks like the following:

    client.insert(:volume,"hugo",{"201202241201"=>{i64(1695656402405)=>""}})

where i64() is a function that packs 64-bit unsigned integers, which in this case is the tweet ID.

To get the volume at a given minute, count the columns:

    >> client.count_columns(:volume,"hugo","201202241201",:count=>MAX_COLUMNS)
    305

The default :count is 100, so if we have a magnitude greater than 100, it’ll get capped. I’ve set MAX_COLUMNS to something high like 999999.

Streaming Insertions with Ruby

The actual processing task is straightforward, but the script is optimized to do the least amount of work possible. This is the key to high-throughput: don’t waste your time and if you can correctly get away with skipping a line, get away with it. Based on the nominees/terms we’re filtering out, we define the group of regular expressions to match against, and then combine them, e.g. [/hugo/, /artist/] becomes /hugo|artist/. Using the group regular expression as a first pass means not having to parse JSON unless we absolutely must.

The crux of the code uses tweet.created_at (e.g., "Thu Mar 06 10:26:58 +0000 2008") to determine the time bucket, e.g. "200803061026". Since consecutive tweets are likely to be close in time, and perhaps in the same time bucket, we take the substring of created_at timestamp up to the minute and memoize the time bucket. In other words, if both the current and last tweets had created_at strings beginning with "Thu Mar 06 10:26", then skip parsing the timestamp and reuse the last time bucket. While this may seem like a micro-optimization, it’s with this mindset that we can maintain a processing rate of hundreds of tweets per second.

How do we measure performance? We could use Ruby’s Benchmark module and measure timing between various points. For a larger picture by way of throughput, we write the insertion script to consume STDIN and combine use the incredibly handy utility called Pipe Viewer, which provides information like throughput about anything that’s being piped:

    $ pv -l event.log | ruby insert.rb
    26.3k 0:01:27 [303.4/s ] [===============>              ] 0:01:30

In this example, pv starts off by counting the lines (-l), and then keeps track of lines seen, the duration and the rate. So far, 26k lines have been processed at a rate of 303k/s, and pv estimates about 1m30 left.

It also works in streaming mode, which is how we use it with a live stream of tweets:

    $ tail -F event.log | pv -l | ruby insert.rb
    26.3k 0:01:27 [303.4/s ] [                <=>                   ]

Meeting in the Middle

Once we have the data in Cassandra, how do we get it out and onto a webpage? If we’re in Ruby, a sane stack might be a Sinatra or Rails app that serves well-formatted JSON right from Cassandra. Given the static nature and finite data set of the visualization though, it was easier to write a script to generate JSON — nay, pure JavaScript! — that provided the series data in a global variable.

While JavaScript code generation in Ruby may seem inelegant, sacrilege or downright insane, working with static files meant being able to initially populate the frontend with dummy data, and figure out the format required by d3. In parallel, we determine how to retrieve the correct data from Cassandra, and finally, generate it in the format needed by d3. Luckily we had last year’s dataset to work with as well, which became integral in the testing and sanity check step.

All in all, it was a whirlwind expedition with two great pieces of open source — Cassandra and d3 — the latter of which deserves its own blog post. Cassandra took a hearty portion of memory but barely broke a sweat handling both insertions and queries.

The Finished Product. Click to Try it out.

Oh and by the way, if you want to build visualizations like this or wrangle terabytes of data, we’re hiring!

The 84th annual Academy Awards were held this weekend. As we’ve seen in years past, Twitter has a lot to say about the Academy Award winners, losers (non-winning nominees?), and the show in general.

This year, we tracked tweets about the Oscars – more than 2 million of them - throughout the show’s broadcast on Sunday, February 26, 2012, and collected them in our Academy Awards Twitter Explorer. Click around the explorer to see when tweets were posted about nominees in six of the main categories, including Best Picture, Best Actor and Best Actress. Or, read on for our take on what Twitter thought of the 2012 Academy Awards.

Twitter’s top ten favorite Oscar 2012 moments were, in order:

During the three-hour awards show, we tracked 2.05 million tweets about the Oscars, with the biggest spike at 18,718 tweets in one minute (during the Cirque du Soleil performance). These numbers are up quite a bit from last year, when the 2011 Oscars garnered 1.27 million tweets and a maximum spike of 11,780 tweets per minute.

The nominees with the most Twitter mentions during the show were:

1. Meryl Streep – 74,793 tweets
2. Octavia Spencer – 59,957
3. Christopher Plummer – 41,107
4. Jean Dujardin – 23,614
5. Rooney Mara – 23,233
6. Brad Pitt – 18,702
7. Viola Davis – 17,651
8. Woody Allen – 14,280
9. George Clooney – 13,252
10. Martin Scorsese – 11,328

The top three films nominated for Best Picture, by tweet volume:

1. Hugo – 110,179 tweets
2. The Artist – 78,509
3. The Help – 23,585

For more information about our interactive explorer, read this blog post about how and what we tracked.