Big Boulder 2013

Posted on May 7, 2013 by Randy Almond, Marketing

Big Boulder’s back for 2013 and better than ever.

The leaders in social data: Facebook, Twitter, Tumblr, Foursquare, Automattic, Disqus and many more are descending on Boulder again this summer to talk about the future of their platforms. Last year was a huge success and the expectations this year are even higher. We have a line-up that will deliver!

We’ll go deep into Asia and Latin America with speakers from China, Brazil and Japan, including the CEO of LINE, one of the fastest growing social networks on the planet. We’ll hear about non-traditional applications of Social Data with discussions on Finance, Government, Academic Research and Data Science. And to help us make sense of it all, we’ll have industry analysts discussing their views of the future. See the agenda and speakers pages for all the details.

In addition to all the great topics covered in the sessions, we’ve left plenty of time for networking with others in Social Data, including sunset cocktails with views of the Flatirons, a bicycle pub crawl, and since this is Boulder after all, morning yoga and hiking.

Big Boulder is an invite-only event for the leaders in the social data ecosystem. Space is filling up quickly so if you’re still thinking about it, sign up now before we hit capacity. Interested in coming but haven’t been invited? First check out our blog post about social data vs. social media. If you’re all about social data, email bre@gnip.com for information.

Social Data vs Social Media

Posted on May 3, 2013 by Elaine Ellis, Marketing

0 comments

One area I see a lot of confusion about is the difference between social media vs. social data. I come from a social media background and use social media in marketing, so I see where the confusion can come from.

The easiest way to think about it in plain English:

Social Media: User-generated content where one user communicates and expresses themselves and that content is delivered to other users. Examples of this are platforms such as Twitter, Facebook, YouTube, Tumblr and Disqus. Social media is delivered in a great user experience, and is focused on sharing and content discovery. Social media also offers both public and private experiences with the ability to share messages privately.

Social Data: Expresses social media in a computer-readable format (e.g. JSON) and shares metadata about the content to help provide not only content, but context. Metadata often includes information about location, engagement and links shared. Unlike social media, social data is focused strictly on publicly shared experiences.

Or otherwise boiled down, social media is readable by humans and made for human interaction while social data is social media that is readable by computers.

Let’s look at a Tweet in form of social media and social data to show exactly what I’m talking about.

From this Tweet from Gnip, we can visually see that it uses the #BigBoulder hashtag, a Bit.ly link to our Storify page, that it has 73 retweets and 3 favorites, the time and date of the Tweet.

Now let’s take a look at what the architecture of a Tweet looks like when received from an API.

{
   "body": "RT @gnip: Thrilled to welcome all #BigBoulder attendees! Watch the social
story unfold on our Storify page. http://t.co/ZzqUMfJz",
   "retweetCount": 71, 
   "generator": {
      "link": "http://twitter.com", 
      "displayName": "web"
   }, 
   "gnip": {
      "klout_score": 53, 
      "matching_rules": [
         {
            "tag": "old krusty tweet", 
            "value": "thrilled to welcome all attendees"
         }
      ], 
      "language": {
         "value": "en"
      }, 
      "urls": [
         {
            "url": "http://t.co/ZzqUMfJz", 
            "expanded_url": "http://storify.com/Gnip/big-boulder"
         }
      ]
   }, 
   "object": {
      "body": "Thrilled to welcome all #BigBoulder attendees! Watch the social
story unfold on our Storify page. http://t.co/ZzqUMfJz",
       "generator": {
         "link": "http://www.tweetdeck.com", 
         "displayName": "TweetDeck"
      }, 
      "object": {
         "postedTime": "2012-06-20T18:07:13.000Z", 
         "summary": "Thrilled to welcome all #BigBoulder attendees! Watch the social
story unfold on our Storify page. http://t.co/ZzqUMfJz", 
      "link": "http://twitter.com/gnip/statuses/215506104082366465", 
         "id": "object:search.twitter.com,2005:215506104082366465", 
         "objectType": "note"
      }, 
      "actor": {
         "preferredUsername": "gnip", 
         "displayName": "Gnip, Inc.", 
         "links": [
            {
               "href": "http://gnip.com", 
               "rel": "me"
            }
         ], 
         "twitterTimeZone": "Mountain Time (US & Canada)", 
         "image": "http://a0.twimg.com/profile_images/1347133706/
Gnip_logo-73x73_normal.png", 
         "verified": true, 
         "location": {
            "displayName": "Boulder, CO", 
            "objectType": "place"
         }, 
         "statusesCount": 971, 
         "summary": "Gnip is the leading provider of social media data for enterprise
applications, facilitating access to dozens of social media sources through a single
API",
         "languages": [
            "en"
         ], 
         "utcOffset": "-25200", 
         "link": "http://www.twitter.com/gnip", 
         "followersCount": 3335, 
         "favoritesCount": 108, 
         "friendsCount": 384, 
         "listedCount": 212, 
         "postedTime": "2008-10-24T23:22:09.000Z", 
         "id": "id:twitter.com:16958875", 
         "objectType": "person"
      }, 
      "twitter_entities": {
         "user_mentions": [], 
         "hashtags": [
            {
               "indices": [
                  24, 
                  35
               ], 
               "text": "BigBoulder"
            }
         ], 
         "urls": [
            {
               "indices": [
                  98, 
                  118
               ], 
               "url": "http://t.co/ZzqUMfJz", 
               "expanded_url": "http://bit.ly/MumrVJ", 
               "display_url": "bit.ly/MumrVJ"
            }
         ]
      }, 
      "verb": "post", 
      "link": "http://twitter.com/gnip/statuses/215506104082366465", 
      "provider": {
         "link": "http://www.twitter.com", 
         "displayName": "Twitter", 
         "objectType": "service"
      }, 
      "postedTime": "2012-06-20T18:07:13.000Z", 
      "id": "tag:search.twitter.com,2005:215506104082366465", 
      "objectType": "activity"
   }, 
   "actor": {
      "preferredUsername": "daveheal", 
      "displayName": "Dave Heal", 
      "links": [
         {
            "href": "http://daveheal.com", 
            "rel": "me"
         }
      ], 
      "twitterTimeZone": "Mountain Time (US & Canada)", 
      "image": "http://a0.twimg.com/profile_images/1755125722/photo_2_normal.JPG", 
      "verified": false, 
      "location": {
         "displayName": "Boulder, CO", 
         "objectType": "place"
      }, 
      "statusesCount": 5657, 
      "summary": "Boulder resident. Rochester NY native. Michigan Law graduate.
Copyright enthusiast. Liker of sports. DFW fanboy. CrossFitter. Work @Gnip. ",
      "languages": [
         "en"
      ], 
      "utcOffset": "-25200", 
      "link": "http://www.twitter.com/daveheal", 
      "followersCount": 671, 
      "favoritesCount": 28, 
      "friendsCount": 292, 
      "listedCount": 26, 
      "postedTime": "2009-03-02T01:18:39.000Z", 
      "id": "id:twitter.com:22432819", 
      "objectType": "person"
   }, 
   "twitter_entities": {
      "user_mentions": [
         {
            "indices": [
               3, 
               8
            ], 
            "id": 16958875, 
            "screen_name": "gnip", 
            "id_str": "16958875", 
            "name": "Gnip, Inc."
         }
      ], 
      "hashtags": [
         {
            "indices": [
               34, 
               45
            ], 
            "text": "BigBoulder"
         }
      ], 
      "urls": [
         {
            "indices": [
               108, 
               128
            ], 
            "url": "http://t.co/ZzqUMfJz", 
            "expanded_url": "http://bit.ly/MumrVJ", 
            "display_url": "bit.ly/MumrVJ"
         }
      ]
   }, 
   "verb": "share", 
   "link": "http://twitter.com/daveheal/statuses/215509188481253376", 
   "provider": {
      "link": "http://www.twitter.com", 
      "displayName": "Twitter", 
      "objectType": "service"
   }, 
   "postedTime": "2012-06-20T18:19:29.000Z", 
   "id": "tag:search.twitter.com,2005:215509188481253376", 
   "objectType": "activity"
}

This is social data. Same content, very different format, very different context and very different end user.

So what exactly does goes into the social data of a Tweet? To start, here is some of the metadata that you’re seeing.

Language identification — It is detected that the language of this Tweet is in English. Language identification is important for social media monitoring so companies can correctly monitor for the content they want.
URL expansion — Essentially this resolves or traces a shortened url to the end url that a consumer would see in their browser window. In this case, http://storify.com/Gnip/big-boulder is the link we shared using bitly.
Content — Gnip shows the full content of the Tweeted message, as well as metadata about the Tweet; like hashtags and URLs used, users that were mentioned, and when it was posted.
User — Gnip provides the display name, username, user’s stated location and additional bio information of the Tweeter. This is the information that users decide to share when signing up for an account.
Klout scores — An additional piece of metadata Gnip can provide is Klout score, so if one of our clients only wanted to see tweets with a Klout score of 30 or higher, they could do that.

Beyond Twitter data, Gnip offers social data from Tumblr, Disqus, Automattic (WordPress) and other publishers that all have their own unique metadata and enrichments. In addition to enrichments, Gnip offers format normalization. This means if you’re looking at a WordPress blog or a Tweet, the data is normalized no matter what the platform. E.g. date and location are formated and located in the same place within the JSON payload; making it easy to consume and parse data from multiple different sources.

Finally, a big difference is in how people use social data vs social media. Social data is what powers social media monitoring and analytics companies, it’s used in business intelligence to combine with other data sets, it’s used by hedge funds as part of their algorithms when looking at financial trades, or even to take a top-level look during a natural disaster.

Access to Public APIs from Instagram, bitly, Reddit, Stack Overflow, Panaramio and Plurk

Posted on April 4, 2013 by Adam Tornes, Product

4 comments

Our customers care about every public conversation that happens online. Every month we deliver more than 100 billion social data activities to our clients. While much of our social data is from our premium publishers (Twitter, Tumblr, WordPress, Disqus and StockTwits), we also make a wide range of social data from public APIs readily available through our Enterprise Data Collector product. A significant part of what Gnip does is make social data easier to digest by optimizing the polling of these APIs and by enriching and normalizing the data. We also normalize the data, so if you’re digesting social data from Gnip from the public API of Instagram, it will appear in the same normalized format as social data from Twitter.

To that end, we’re announcing the addition of the public APIs for Instagram, bitly, Reddit, Stack Overflow, Panaramio and Plurk to the Gnip Enterprise Data Collector. While some of those might make perfect sense to you, others might make you turn your head and say, “huh.” Below we have more background on each publisher and why they’re important to the social data ecosystem.

Instagram on Enterprise Data Collector

This photo sharing app, recently acquired by Facebook, continues to be one of the fastest growing social networks out there with 90 monthly million active users. Every day there are 40 million photos uploaded, and every second users like 8,500 photos and make 1,000 comments about them. Our customers have traditionally been very interested in geotagged social data, and between 15 to 25 percent of Instagram users geotag their photographs.

Instagram has become a popular marketing tool for brands from Anthropologie, Intel, Virgin America, Taco Bell and American Express to name a few with Instagram accounts. Furthermore, we’ve really started to see Instagram as a popular tool around current events and for citizen reporting. During Hurricane Sandy, many people used Instagram as a way to document what was happening around them and showing destruction in real time. With the recent inauguration, CNN asked users to tag their Inaugural Instagram photos with #CNN and they saw users submitting an average of 25 photos every few seconds.

Customers accessing the Enterprise Data Collector will be able to access popular posts, conduct tag searches and geosearches.

Potential Uses for the Instagram API:

Tracking photos around natural disasters
Geo use cases for a given location
Brand monitoring

bitly on Enterprise Data Collector

bitly is the easiest and most fun way to save, share and discover links from around the web. While commonly associated as a link shortener for Twitter, bitly is used across the web and provides great information about what social sites are driving traffic. People use bitly to share 80 million new links a day.

Gnip customers will be able to search keywords some of destination page title and URL and some of the content and header tags.

Potential Uses for the bitly API:

Monitoring for brand mentions
Understanding trending content

Reddit on Enterprise Data Collector

Reddit is a social news site with user-generated content covering nearly every topic in the world. One of the world’s fastest growing sites in the world, Reddit has 50 million active users contributing links, stories, pictures and topics of discussion.

Customers will be able to search by keyword and hot topics. Brands are often unaware of stories percolating about them on the popular site. One recent interesting example is where a Redditor posted an Applebee’s receipt where a pastor refused to tip her waitress based on how much she was tithing, which ultimately ended up being a national news story.

Potential Uses for the Reddit API:

Monitoring for brand mentions
Crisis communications warning

Stack Overflow on Enterprise Data Collector

Stack Overflow is a community edited Q&A site about computer programming, making it easy for programmers to find answers to questions they have about code. The site has more than 1.5 million registered users and 4 million questions.

Customers will have access to the entire firehose of Stack Overflow Answers and be able to search tags, reputation and comments by keyword. Programmers tag their questions and making it easy to find the content you’re looking for. Currently, the six most popular tags are C#, Java, PHP, JavaScript, jQuery, and Android.

Potential Uses for the Stack Overflow API:

Monitoring questions and discussion about software and technical brands
Monitoring bugs and outages
Often requested in conjunction with review sites

Panoramio on Enterprise Data Collector

Panoramio is a photo-sharing website with geotagged content that is layered upon Google Earth and Google Maps. Panoramio allows viewers to see an enhanced view of Google Earth because they can see other photos taken in the area.

Customers will be able to use a bounding box to view photos within a certain location. We have consistently found that our customers are eager for more social data with geotagged content.

Potential Uses for the Panoramio API:

Monitor social activity within a certain geographic area

Plurk on Enterprise Data Collector

Plurk is a microblogging site that allows users to communicate in posts with 210 characters and emoticons. Plurk has more than 1 million active users that post 3 million “Plurks” each day. Plurk is one of the more popular social networks in Taiwan and also has a strong presence in Hong Kong, Singapore, Philippines and India. Gnip customers will be able to search for keywords within posts.

Potential Uses for the Plurk API:

Monitoring for brand mentions, with a particular focus on certain Asian countries
Understanding trending content

If you’re interested in learning more about these additional sources on Enterprise Data Collector, please contact info@gnip.com for more information.

4 Things You Need To Know About Migrating to Version 1.1 of the Twitter API

Posted on February 21, 2013 by Adam Tornes, Product

0 comments

Access to Twitter data through their API has been evolving since its inception. Last September, Twitter announced their most recent changes which will take effect this coming March 5. These changes make enhancements to feed delivery, while further limiting the amount of Tweets you can get from the public Twitter API.

The old API was version 1.0 and the new one is version 1.1. If your business or app relies on Twitter’s public API, you may be asking yourself “What’s new in Twitter API 1.1?” or “What changed in Twitter API 1.1?” While there’s not much new, a lot has changed and there are several steps you need to take to ensure that you’re still able to access Twitter data after March 5th.

1. OAuth Connection Required
In Twitter API 1.1, access to the API requires authentication using OAuth. To get your Twitter OAuth token, you’ll need to fill out this form. Note that rate limits will be applied on a per-endpoint, per-OAuth token basis and distributing your requests among multiple IP addresses will not work anymore as a workaround. Requests to the API without OAuth authorization will not return data and will receive a HTTP 410 Gone response.

2. 80% Less Data
In version 1.0, the rate limit on the Twitter Search API was 1 request per second. In Twitter API 1.1, that changes to 1 request per every 5 seconds. A more stark way to put this is that previously you could make 3600 requests/hour but you are now limited to 720 requests/hour for Twitter data. Combined with the existing limits to the number of results returned per request, it will be much more difficult to consume the volume or levels of data coverage you could previously through the Twitter API. If the new rate limit is an issue, you can get full coverage commercial grade Twitter access through Gnip which isn’t subject to rate limits.

3. New Endpoint URLs
Twitter API 1.1 also has new endpoint URLs that you will need to direct your application to in order to access the data. If you try to access the old endpoints, you won’t receive any data and will receive a HTTP 410 Gone response.

4. Hello JSON. Goodbye XML.
Twitter has changed the format in which the data is delivered. In version 1.0 of the Twitter API, data was delivered in XML format. Twitter API 1.1 delivers data in JSON format only. Twitter has been slowly transitioning away from XML starting with the Streaming API and Trend API. Going forward, all APIs will be using JSON and not XML. The Twitter JSON API is a great step forward as JSON has a much wider standardization than XML does.

All in all, some pretty impactful changes. If you’re looking for more information, we’ve provided some links below with more details. If you’re interested in getting full coverage commercial grade access to Twitter data where rate limits are a thing of the past, check out the details of Gnip’s Twitter offerings. We have a variety of Twitter products, including realtime coverage and volume streams, as well as access to the entire archive of historical Tweets.

Update: Twitter has recently announced that the Twitter REST API v1.0 will officially retire on May 7, 2013. Between now and then they will continue to run blackout tests and those who have not migrated will see interrupted coverage so migrating as soon as possible is highly encouraged.

Helpful Links
Version 1.0 Retirement Post
Version 1.0 Retirement Final Dates
Changes coming in Twitter API 1.1
OAuth Application Form
REST API Version 1.1 Resources
Twitter API 1.1 FAQ
Twitter API 1.1 Discussion
Twitter Error Code Responses

Data Stories: Brooke Fisher Liu on Using Social Media in Natural Disasters

Posted on February 19, 2013 by Elaine Ellis, Marketing

0 comments

Data Stories is Gnip’s project to tell the stories of how social data is being used. This week we’re interviewing Brooke Fisher Liu from the University of Maryland about her research on how people use social media in natural disasters (PDF). You can follow Brooke on Twitter at @Bfliu. (Also, you can see our data scientists post on Twitter’s reaction to an earthquake in Mexico.)

Brooke Fisher Liu (photo courtesy of Anne McDonough)

1. When the wildfires broke out in Boulder, I found Twitter to be the best source of information hands down. What kind of information do you see people communicating about natural disasters?

During natural disasters people tend to use social media for four interrelated reasons: checking in with family and friends, obtaining emotional support and healing, determining disaster magnitude, and providing first-hand disaster accounts. A consistent research finding is that people are less likely to follow official, government sources on social media than their friends and family during disasters. I think that may change over time as government sources become more savvy about effectively using social media during disasters.

2. How is curated content such as Storify changing how people communicate during disasters?

This is one area where the research hasn’t caught up with practice yet. However, I think that social media sites that curate content such as Storify, Pinterest, or even Instagram are going to be major players in disaster communication in the future. One of the reasons people don’t turn to social media for disaster information is that the quantity of information is difficult to sift through and verify. Sites that curate content help cut through the sea of online information, and also provide a familiar, reliable source of information through online connections established before disasters.

3. You talked about people mobilizing on social media after natural disasters in your report. Do you ever see people respond in real time?

Absolutely. Real-time communication is one of the primary draws of social media during disasters. There are multiple examples of social media being the first source of disaster information such as for the 2011 Tuscaloosa tornadoes and the 2008 Mumbai terrorist attacks.

4. What surprised you the most about how people were using social media during natural disasters?

By far the biggest surprise is that people still turn to traditional media sources, especially broadcast journalism, as the most accurate source of disaster information. So, while they may first turn to social media, they still prefer traditional media during disasters. I think this may change over time, but it certainly was a surprise for me. Of course, journalists often rely on social media for disaster information, and I think over time we’ll see the distinction between traditional media and so-called new media blur even more.

5. How do you think the use of social media in natural disasters will evolve?

I think over time people will view social media as more trustworthy and thus turn to it as their primary source of information. I also think social media will continue to play a large role in facilitating disaster recovery by helping people connect with each other and rebuild communities. “Official sources” such as governments and the media will increasingly enhance their social media presence before disasters, which likely will position them to be not only the first, but also most trustworthy social media sources down the road. Perhaps most importantly I think social media will continue to surprise us by providing new communication capabilities during disasters that we can’t currently predict.

Continue reading →

Observations On Disqus: The Spread of Words

Posted on February 6, 2013 by Elaine Ellis, Marketing

0 comments

Marketers and communicators all share a similar goal: to become part of the conversation. Comments in reaction to blogs and news stories are a fantastic place to discover the topics that are driving conversation. To dig deeper, we recently looked at public comments from Disqus, the world’s largest discussion platform, to see what was getting online chatter at the end 2012. With 70,000 comments published on Disqus every hour, you can find insights and conversations that can’t be found elsewhere.

What we found is that communicators often use a language set that the audience does not share. In discussion, most common denominator language dominates. Let’s look at a couple of examples.

The Fiscal Cliff

At the end of 2012, one topic that dominated mainstream publications and political blogs was the Fiscal Cliff, when a series of tax cuts for the United States were expected to expire at the end of the year. Since this was a topic of contention between the Democrats and Republicans, you would have expected this to be a passionate point of conversation during the Elections. As it turns out, this wasn’t exactly the case. When did the Fiscal Cliff talk start? The day after the Election. And the discussion was couched in broader terms than just the acute “Fiscal Cliff” crisis. So while Washington operates and speaks in continual crisis mode, the public thinks of these challenges in broader, more systemic terms.

While the Fiscal Cliff wasn’t a hot topic until after the election, taxes and medicare saw consistent conversations before and after the election.

Timing is everything when it comes to starting conversations. While the Election focused on what happened in the past four years and what would happen in the next four years, the day after the Election honed in on what was immediately down the road — the Fiscal Cliff.

Skyfall vs Breaking Dawn vs Twilight

Moving from politics to pop culture, we were curious what would generate more conversation — a bunch of sparkly vampires driving Volvos (the movie Breaking Dawn, the fourth installment in the Twilight series) or the eponymous spy from England (Skyfall). We were initially surprised to see that Skyfall generated more chatter around its premiere on Nov. 9 than Breaking Dawn saw for its premiere on Nov. 18. However, when we took a closer look by adding the term Twilight into the mix, we found that Twilight created more chatter than Skyfall.

Comments are an excellent barometer of buzz around upcoming events and launches. Even more than that, comments can help companies understand what terms people use about an event. In this example, if you were the studio marketer using content marketing to promote the release of Breaking Dawn, your odds would improve by using Twilight in your headline.

Movie Vs. Libya vs. Benghazi

While searching for popular movies on Disqus, we found an interesting spike for the term “movie” in mid-September, but couldn’t attribute it to a popular movie. After some digging, we realized that this was related to the movie “Innocence of Muslims,” the controversial spoof movie on the religion. While the movie was originally uploaded to YouTube in July, it aired on an Egyptian network on Sept. 9, which immediately created protests that quickly spread to Libya. On Sept. 11, four Americans including the Ambassador were killed in Benghazi, Libya. While the terms Libya and movie spiked immediately, Benghazi built up momentum more slowly over time spiking right before the election as it became part of the political debate between the two parties.

Buzz around current events doesn’t immediately spike right after the event. As new facts and information are disseminated, the current of conversation can change. In this scenario, a new and more specific term “Benghazi” did dominate the conversation, as it slowly became shorthand for the overall issue. What carries conversation is language that accelerates understanding and lowers the barrier for participation.

Ultimately, comments are windows into not only what people are talking about but also when topics tip over into public conscious and what the driving forces are behind when conversations peak. In the same way that communicators deploy search engine optimization to target searchers, they need to also incorporate conversation optimization strategies to become part of the conversation.

Super Bowl Social Media Roundups

Posted on February 4, 2013 by Elaine Ellis, Marketing

1 comment

Yesterday’s Super Bowl XLVII created more Twitter traffic than the three presidential debates combined. In fact, according to the Twitter blog, during the power outage there was 231,500 Tweets per Minute. MarketingLand even found that Twitter was mentioned in 50% of Super Bowl commercials. Twitter wasn’t the only one seeing interesting spikes and data science around the Super Bowl. Tumblr had its own Uberbowl Tumblr allowing users to tag #SuperBowl and sharing the best of the posts. Facebook did data science around the Facebook fans of NFL teams and the two Super Bowl contenders.

Below we’re sharing the analysis we’ve seen around social media and the SuperBowl and we will keep updating this post through out the day. Leave us a comment in the links if you know of additional analysis!

Ad Age and Bluefin Labs: Top 10 Super Bowl Ads on Social Media - Showed which commercials created the most social media conversation in the 45 minutes after the commercials aired.

AdWeek and Attensity: Taco Bell, Doritos Dominated Super Bowl Social Media - They found Doritos was the most mentioned brand among a variety of social media channels.

Hootsuite: Super Bowl XLVII Command Center – Shows Twitter comparisons between the two teams, as well as sentiment.

Netbase: Harbowl? More Like Social Media Super Bowl - A brand passion index showing the most popular commercials on social media.

Networked Insights: Post Game Analysis – Top Brands & Celebrities from Super Bowl XLVII: Takes a look at the most talked about moments on social media, a close look at Beyonce’s Half-Time Show, most popular celebrities and more.

Nielsen: Tweets, Spots and Carrot Sticks: the Modern Super Bowl - Sixty-two percent of consumers also said they plan to use social media to comment on the game as the teams compete. Also, shows the top snacks people were planning on consuming.

MarketingLand: Game Over: Twitter Mentioned in 50% of Super Bowl Commercials, Facebook Only 8%, Google+ Shut Out

Simply Measured: When the Lights Went Out, Social Brands Lit Up - Simply Measured looked at how brands engaged during the game and what the top mentioned brands were on social media.

Trendrr: Super Bowl XLVII is the Most Social TV Telecast Ever - An infographic comparing 2012 social media to 2013 social media traffic.

Union Metrics: Beyonce Wins the Super Bowl; Pepsi Wins Tumblr - This post talks about the more than one million Tumblr users that posted nearly 1.5 million posts Super Bowl related posts yesterday and their main topics of conversation.

Visible Technologies and Exact Target: Beyonce, Power Outage and Baltimore Ravens Win Social #SuperBowl (#infographic) - Great infographic sharing the winners and losers of the Super Bowl including my favorite – which Harbaugh brother won on social media.

Visible Technologies: How did people really feel about the Super Bowl? Unsurprisingly, the power outage had a 80% negative sentiment.

Introducing PowerTrack for Tumblr

Posted on November 15, 2012 by Rob Johnson, Product Development and Strategy

0 comments

Gnip is introducing a solution to make it even easier to find the Tumblr data you want to see. We’re introducing PowerTrack for Tumblr, a way to filter specific content. Tumblr is an unbelievable source of social data with more than 70 million new posts every day. Similar to PowerTrack for Twitter, PowerTrack for Tumblr will deliver full coverage of the posts you want based on the filtering criteria you create.

With PowerTrack for Tumblr, you can filter Tumblr data by not only keyword, but also by specific Tumblr blogs. This means if a brand wants to track the content on their Tumblr, they can track activity and reblogs around that specific Tumblr. In addition, users can track specific URLS, so if you’re a brand you can watch for all links to your company page. With Tumblr’s seven post types (text, photo, quote, link, chat, audio, video), it’ll now be possible to hone in on specific post types. If you’re only interested when a song is posted, now it’ll be even easier to track. You can read all of the specific filtering rules available on Gnip’s documentation.

After we announced the launch of the Tumblr firehose in April of this year, we’ve been blown away by the uniqueness and richness of Tumblr content and how active their community is. And the Tumblr analytics space is evolving quickly with the launch of Union Metrics for Tumblr several weeks ago. We know that content on Tumblr can be incredibly viral and sticky due to the ability to reblog and tag content. Whether brands have an official presence on Tumblr or not, they’re going to be mentioned there. We’re excited to offer a product that makes it easier to find mentions and content. Check out the details on your own or email us at sales@gnip.com to learn more.