The Facebook Blog
Today we're excited to preview the next version of Lexicon. With over 100 million active users on Facebook, Lexicon graphs are a powerful way to understand the trends in what people are talking about. We've introduced a number of new ways to play with the data in this version, and many of the enhancements are based on your feedback over the last couple of months.
Lexicon only gathers text from Walls and never accesses messages, Chat, searches, or other private data. All the information is aggregated so it is never tied to a specific person. This gives you the ability to hear the diverse voices of Facebook without singling out individual people.
One of the most frequent suggestions we received was to show exactly how many times each topic was mentioned, so we now show you a Dashboard with the total number of unique users who mentioned a topic, as well as the percentage of our user base that mentioned the topic and the total number of posts. You can use the Demographics feature to follow the trends over time between users of different ages, genders, and countries. The Maps feature shows you where people are talking about a topic within different countries.
The Sentiment feature shows how much people like or dislike a given topic. You can compare two topics to see how the sentiment about each topic matches up. The Associations feature allows you to see words and phrases that are closely associated with a topic in different points in time. Finally, the Pulse feature highlights keywords that frequently show up in the Profiles (Interests, Music, etc.) of people who are talking about a topic on Walls.
Lexicon only gathers text from Walls and never accesses messages, Chat, searches, or other private data. All the information is aggregated so it is never tied to a specific person. This gives you the ability to hear the diverse voices of Facebook without singling out individual people.
One of the most frequent suggestions we received was to show exactly how many times each topic was mentioned, so we now show you a Dashboard with the total number of unique users who mentioned a topic, as well as the percentage of our user base that mentioned the topic and the total number of posts. You can use the Demographics feature to follow the trends over time between users of different ages, genders, and countries. The Maps feature shows you where people are talking about a topic within different countries.
The Sentiment feature shows how much people like or dislike a given topic. You can compare two topics to see how the sentiment about each topic matches up. The Associations feature allows you to see words and phrases that are closely associated with a topic in different points in time. Finally, the Pulse feature highlights keywords that frequently show up in the Profiles (Interests, Music, etc.) of people who are talking about a topic on Walls.

Associations with "Baseball"
To help you understand the power of this new tool, we have included several topics to play around with. In the coming weeks and months, we'll be opening up many more topics and supporting additional demographics and countries.
We're still working on Lexicon and would love to hear what you think as you explore, so give us a shout with your thoughts.
Roddy is following the election right here on Lexicon.
At Facebook we love tools that allow you to see what people around the globe are searching for or discussing on blogs, such as Google Trends or Technorati. We thought it would be cool to show trends on the public and semi-public forums across Facebook (also known as Walls). Today we're announcing the launch of Facebook Lexicon, a tool where you can see the buzz surrounding different words and phrases on Facebook Walls. Lexicon pulls from the wealth of data on Facebook without collecting any personal information in order to respect everyone's privacy.
The Wall is a really interesting place to look for buzz, because when one person writes a post on a friend's or a group's Wall, tens, hundreds, or even thousands of people might see it; those viewers may read, digest, and pass on that information, spreading it virally. So when my friend Kasey wrote on my friend Blaise's Wall saying how she really liked the movie Juno, I saw her post and knew I had to see it for myself. It seems like a lot of users share her sentiments; excitement about the movie grew significantly when it was released in early December:
The Wall is a really interesting place to look for buzz, because when one person writes a post on a friend's or a group's Wall, tens, hundreds, or even thousands of people might see it; those viewers may read, digest, and pass on that information, spreading it virally. So when my friend Kasey wrote on my friend Blaise's Wall saying how she really liked the movie Juno, I saw her post and knew I had to see it for myself. It seems like a lot of users share her sentiments; excitement about the movie grew significantly when it was released in early December:

How are these numbers calculated? We have a cluster of computers that count the number of occurrences of every term (for example, "juno") across profile, group and event Walls every day. The system strips out all personally identifiable information so that there is no way to track a mention back to a specific person. No human at Facebook ever reads these Wall posts, and Lexicon does not look at personal messages, invitations, or any other private user-to-user communications.
Play around with Lexicon. You can compare up to five different words or two-word phrases and see how many people talked about that term each day. As long as enough people mentioned the term, it will show up on the graph. Want to see how many people are talking about going skiing vs. going to the beach? Go for it.
Roddy, a Facebook Engineer, is comparing apples to (blood) oranges.
Archived Posts by Date
2009
November (12)
October (17)
September (10)
August (10)
July (10)
June (13)
May (13)
April (13)
March (14)
February (13)
January (8)
2008
December (15)
November (14)
October (12)
September (9)
August (2)
July (3)
June (6)
May (5)
April (6)
March (2)
February (4)
January (3)
2007
December (4)
November (4)
October (1)
September (3)
August (4)
July (4)
June (2)
May (5)
April (9)
March (8)
February (7)
January (4)
2006
December (3)
November (6)
October (5)
September (7)
August (4)
Archived Posts by Blogger
Abraham Cooper (1)
Adam Conner (4)
Adam Hupp (1)
Aditya Agarwal (2)
Akhil Wable (1)
Alex Moskalyuk (1)
Alexandre Roche (3)
Alok Menghrajani (1)
Annie Ta (2)
Ari Steinberg (2)
Arjun Banker (1)
Austin Haugen (1)
Barbara Fischkin (1)
Barry Schnitt (1)
Benjamin Ling (1)
Bikash Agarwalla (1)
Blair Heuer (1)
Blaise DiPersia (1)
Blake Chandlee (1)
Bo Hong Deng (1)
Bob Trahan (2)
Brian Shire (1)
Brynn Shepherd (1)
Cameron Marlow (1)
Carl R. Augusto (1)
Carolyn Abram (11)
Cat Lee (3)
Chad Little (2)
Chengos Lim (1)
Chris Cox (2)
Chris Hughes (2)
Chris Kelly (4)
Chris Putnam (3)
Chris Ward (1)
Craig Donato (1)
Dan Rose (1)
Daniel Chai (1)
Danna Gutman (1)
Dave Fetterman (1)
Dave Morin (1)
Doug Beaver (2)
Dustin Moskovitz (1)
Elizabeth Linder (2)
Elliot Schrage (2)
Eric Kwan (1)
Eric Zamore (1)
Evan Priestley (1)
Everett Katigbak (1)
Ezra Callahan (8)
Florin Ratiu (1)
Gareth Davis (1)
Gene Fant (1)
Ghassan Haddad (1)
Gibson Biddle (1)
Graeme Menzies (1)
Harry Huai Wang (4)
Henri Moissinac (1)
Jack Lindamood (1)
Jake Brill (1)
James Wang (2)
Jared Cohen (1)
Jason Min (1)
Jason Sobel (1)
Jeff Kanter (1)
Jeff Williams (1)
Jeffrey Wieland (1)
Jesse Dwyer (1)
Jessica Ghastin (1)
Jimmy Lavoie (1)
Joanna Lee (1)
Joe Green (1)
Joe Hewitt (3)
Joe Sullivan (1)
Joel Seligstein (1)
Jon Fougner (2)
Jon Warman (2)
Jonathan Hsu (1)
Josh Elman (1)
Josh Wiseman (2)
Julie Trescott (1)
Julie Zhuo (2)
Justin Bishop (1)
Justin Mitchell (1)
KC Estenson (1)
Kari Lee (1)
Kate Losse (3)
Kathy H. Chan (4)
Katie Carter (2)
Katie Geminder (6)
Kevin Arata (1)
Kevin Der (1)
Leah Pearlman (5)
Lee Byron (1)
Lisa P. Jackson (1)
Liz Perle (1)
Luke Shepard (1)
Makinde Adeagbo (1)
Malorie Lucich (1)
Marcia Velencia (1)
Mark Kinsey (2)
Mark Slee (9)
Mark Zuckerberg (18)
Matt Cahill (1)
Max Kelly (3)
Melissa Luu-Van (1)
Melody Quintana (1)
Michael B Kaiser (1)
Michael Gummelt (1)
Michael Richter (1)
Mike Honda (1)
Naomi Gleit (4)
Natalie Minor (1)
Navid Mansourian (1)
Nico Vera (3)
Nikki M. Flatley (1)
Paul C. Jeffries (1)
Paul Janzer (1)
Paul McDonald (1)
Pedram Keyani (1)
Pete Bratach (1)
Peter X. Deng (2)
Philip Fung (3)
Prashant Malik (1)
Randi Zuckerberg (5)
Raylene Yung (1)
Richard Allan (1)
Rob Goodlatte (1)
Robert Johnson (1)
Roddy Lindsay (2)
Ruchi Sanghvi (1)
Ryan McGeehan (3)
Sam O'Rourke (1)
Sameer Moidu (1)
Sandra Liu Huang (1)
Sara Lannin (3)
Sasha Rosse (1)
Scott Marlette (1)
Scott Mills (1)
Shaun King (1)
Shervin Pishevar (1)
Sheryl Sandberg (1)
Simon Axten (3)
Sophia Huang (1)
Steven Grimm (1)
Suzie White (1)
Ted Ullyot (1)
Teddy Underwood (1)
Tim Sparapani (1)
Tom Occhino (1)
Tom Whitnah (4)
Victor Valdez (1)
Wayne Chang (3)
Will Chen (3)
Xenia Nosov (1)
Yair Landau (1)
Yishan Wong (1)

