Visualizing Changes in Meaning

By Eric Bell,Natural Language Processing Software Scientist at Pacific Northwest National Laboratory and BBI Board Member, Dr. Seuss, Jeggings, and Dill?

“So the writer who breeds
more words than he needs
is making a chore
for the reader who reads.”

-Dr. Seuss

Humans are social creatures, and social implies communication.  We communicate in many forms: words, pictures, gestures, etc., but language, and words, are at the center of all communication.

From Dr. Seuss to William Shakespeare, humans have been making up and playing with words for centuries.

Words can change meaning over long periods of time. For example, the word “awful”, used to mean worthy of awe. Other words change meaning in a matter of moments. Would your definition of “computer” include your phone?

While today’s millennial may be chillaxing in their jeggings, unfriending vestiges of a failed bromance, computers around the world are racing to understand what all of the new words in the first part of this sentence mean.  If computers are going to understand humans, they must understand what words mean, and that includes when words change their meaning.

Researchers at Pacific Northwest National Laboratory have been examining this phenomenon, known in academic circles as semantic shift.

Words, like technology, are evolving faster than before. Communication in modern society is characterized by an always-on, constant barrage of global conversations.  This is compounded by the recent transition from face-to-face and point-to-point telephone conversations to multiple consumer communications in the rise of social media and mobile messaging platforms.

These changes in communication styles have given rise to a number of phenomena including emojis, live video streaming from around the globe, and a world of shopping with reviews at your fingertips.

The approach to understanding the meaning of a new word was traditionally accomplished by examining its relationship or shared grammatical constructions with known words. This approach is called statistical semantics. For example, from the phrase “wear jeggings to work” a computer can infer that jeggings are most likely a piece of clothing, because a clothing-related word often follows the verb “wear”.  When this sort of reasoning is applied over billions of social objects every day, new words can quickly be assigned some meaning.

As that meaning slowly changes with the adoption of words and the natural process of semantic shifts, a backward look in time at a word’s meaning today can help explain its origins and historical relevance.

At PNNL, scientists have been exploring the use of new terms in a variety of social data platforms, focusing on techniques from statistical semantics that aren’t platform or language dependent.

We’ve taken a technique called ‘temporal embeddings’ and combined that with novel visualization techniques to produce visual summaries of a word’s semantic shift, focusing on some words that have rapidly changed meaning in recent events.  Below we present a visualization of the term ‘ukrop’ which during the Crimean Crisis went from being a term describing the spice dill to an insult for Ukrainians. The path illustrates how the meaning of ‘ukrop’ meanders through a concept space in a relatively short period of time.


Here’s another example of how the word ‘fire’ shifted from ‘a natural disaster’ to ‘gunfire’.



Both of these examples are based on examination of social data during the Crimean Crisis, gathered from VKontakte, Europe’s largest social networking service.

Like words themselves, our process is evolving. And we want you to help. Do these images help explain the origin of a term?   These depictions are snapshots of an interactive system that lets you look at multiple words in the same concept space or representation of word meanings.   We invite the industry to help take the next step, the exploration of a similar phenomenon in the significance and meaning of visual social content.

So you readers who read
more words than we need,
fear not these new words
computers can help explain the misdeed.



BBI November/December Events

BBI Community –

Only 17 days until Coca-Cola’s Data Summit! Registration is free and you can register here.  BBI is very fortunate to have Justin De Graaf of Coca-Cola on our board and because of our good fortune, you have access to this incredible event. We have confirmed the following amazing speakers.

The topics that will be covered are . . .

  • What’s My Name? A day in the life of data: What data is worth purchasing? So many vendors where does one start?
  • 99 Problems: Programmatic & Direct Advertising: How does the industry toe the line? Am I over or under invested?
  • The Symphony: Are you listening? Making Sense of Social Data
  • Paid in Full: Closing the loop for CPG companies: measuring marketing w/ dollars and sense
  • DMPs and the New World Order: How marketers from various industries are leveraging Data Management Platforms.
  • The Revolution Will Not Be Televised: Where to invest in linear, digital video or addressable?
  • Follow the Leader: Making the most of mobile (targeting, marketing and measurement)
  • A Good Day: Telling Better Stories with Data

The event will be held on November 17th, at The Roberto Goizueta Auditorium, Coca-Cola HQ. The address is 1 Coca-Cola Plaza, Atlanta, GA 30313. Please email me at mike@bbi.org for more information.

BBI Meetups

Our Social Data and Analytics Meetups have another round coming in early December.

  • New York: we are focusing on the Food and Beverage industry. Details are here
  • Washington DC: we are focused on leveraging Social Data for Social Good. Details are here
  • San Francisco: we are meeting up to discuss the details behind uncovering influencers in Social Data. Details are here

If you would like to participate – we would love to have you either host or present one of these well attended Meetups. Please contact  Patrick Callahan at Patrick@compassRed.com or me at mike@bbi.org.



Flip Back to the Future

By Tyler Singletary, BBI Board Member and VP & GM Klout and Consumer Data, Lithium (@harmophone, Klout, Lithium

Flipboard was the first killer app for the iPad — a beautiful new way to read content from across the web, without worrying about RSS feeds. It was an early innovator at leveraging social networks for personalization. And it just might be the canary in the coal mine in a number of ways.

While Facebook gets mired in a debate around its use of human curators, and again deeper in its use of algorithmic curation, Flipboard had already gotten us familiar with both — and without the backlash. It’s been awhile since one finds a completely irrelevant article, and it’s learned what sources you read, the topics you’re interested in, the amount of time you’re reading — nearly everything that optimizes a discovery and personalization system.

Flipboard’s native National Geographic experience, putting up the wall one brick at a time.

To accomplish this, we were lead through the gates of their walled garden. Don’t be afraid, they’re pretty good gardeners. Early Flipboard users remember a time when a decent amount of content wouldn’t render well. Limitations with the IOS browser, content crawling and classification, and inherent hardware problems presented some downright ugly content and application crashes. To drive a more consistent user experience, Flipboard introduced a few features that sound familiar in today’s world of OpenGraph tags, Instant Articles, Twitter Cards, and Pinterest optimization: custom Flipboard CSS tags and a content partnering platform with select publishers — to beautify and provide a native experience to users. Flipboard became a platform. It also gave them their first ad monetization opportunities.

Walled gardens aren’t usually made with bad intentions. Most people are just happy to see the foliage. It tends to rankle the open web purists though, and certainly gives engineers a lot more to consider. What if web standards are behind? What if users don’t actually care about a standards-compliant, utopian free web, and just want to see their content? Then there are the paywalled gardens, like the Wall Street Journal and The New York Times. While germinated from a more protectionist point of view, they’re fighting for survival. Users don’t want to see ads, but they want content for free. Open Web enthusiasts seem happy with simple RSS readers and ignore the window dressing that content creators have the right to be viewed. Flipboard remains one of the only platforms purely dedicated to aggregated content discovery and consumption, with Apple News taking their playbook since IOS9. In this game, the platform with the most eyeballs and the best relationships with publishers will win.

And this is where Flipboard may be an early warning system. We’ve seen a number of other “newsreader” tools fall by the wayside and be shut down, already. If Flipboard loses this battle, it isn’t because of their approach to personalization — it worked, and social data had one of its first proof of concepts (and corrections: Flipboard was smart enough to ask its users about their interests, too). It isn’t because of their deals with publishers — that was survival, good business sense, and a model Facebook and Apple adopted. But its peer-to-peer social features and curated magazines, perhaps its only unique features against Apple (with Nuzzelon its heels), aren’t essential to the experience. Apple has won these arms wars in the past through shrewd licensing. Ironically, Open Web concepts may be the saving grace that keeps Flipboard in the game.

Facebook is betting users will only care about the news as a passing interest amongst their friends, with Twitter focused on breaking the news, not just sharing it. LinkedIn thinks it’s part of an authored thought leadership forum. Apple will integrate it tighter with iMessage, but gave us the “just the facts, ma’m” version. If anyone dies in this mine, it’s not because there’s gas poisoning, it’s because there just isn’t enough clean air to breath. The users will read pretty, relevant content wherever and however it appears. The more seamless, the better.


How Digital Curation Enhances the Value of Social Data

By Leigh Fatzinger, CEO, Turbine Labs (@lfatzinger, @turbinelabs)

Over the last 10 years, the social data market sector has enabled a multitude of ways to understand how audiences interact with brands, organizations, political candidates, governments, and more.  Social data platforms have expanded in functionality and complexity through investment and industry consolidation, while simultaneously adjusting to new and evolving data sources. In the case of Facebook and Twitter, the availability or restricted use of existing data sources has required platforms to divert from their original product roadmaps. Even with the changing data access landscape, social data platforms have access to a staggering amount of consumer and media content – data that needs to be collected, filtered, and processed into a usable format.

From an innovation perspective, and as a response to the amount of data available, much attention has been paid to enhancing and simplifying the user experience of these platforms with the goal of attracting and maintaining the widest possible audience of analysts, researchers, brand managers, subject matter experts, and others.

Attention has also been given to automating, as much as possible, the results delivered by these platforms once configured for an entity or use case. Fulfilling the ‘ease of use’ benefit that many platforms tout as differentiators, users have come to expect that producing and consuming useful insights should require no more than one or two clicks of a mouse.

At the same time, users of social data platforms continue to face headwinds when it comes to answering key value-oriented questions: What should we be measuring? What are the right KPIs? What is the expected outcome of the data we collect? Do reports generated by our chosen platform align to business goals? Are these insights actionable?

Access to massive amounts of data, the pressure users have placed on platform developers to simplify user experience, the expectation of automation, as well as the near real-time need for actionable intelligence, is driving the market to an inflection point – an inflection point that will change how these platforms are used to justify their investment.

Today, new questions are emerging that focus more on topical context and relevancy rather than vanity metrics such as audience growth and engagement rates. Yes, users of these platforms continue to measure, with good reason, how many shares and retweets their owned content generates. They continue to count earned media placements. They continue to plan and generate content with an expectation of virality.

But increasingly, brands, organizations, and governments are realizing that the definition of insights is achieved through a granular, contextual understanding of how audiences respond to a campaign or topic. Users need to be able to quickly and efficiently digitally curate massive amounts of data in a very short time to be able to extract truly relevant and actionable insights from the data.

Digital curation begins by configuring and tuning social data platforms to listen not only for a brand, organization, candidate, etc., but to categorize media and consumer conversations on a campaign-by-campaign or topic-by-topic basis. The output of these categorizations enables an analyst or researcher to make a baseline comparison against the total conversation as well as understand the overall sentiment of the topic.

The real value of digital curation comes from leveraging software to enable humans to quickly analyze and process a subset of the categorized data to determine the tone, narrative, and impact of the campaign or topic as a whole. The software offers access to the data, while humans extract unique, contextual elements of the data to make it useful and actionable. Through digital curation, the reporting of insights becomes more than just raw performance numbers on a campaign or topic. Results can be presented in a more persuasive way by presenting stakeholders with what consumers, media, and competitors are actually saying within the context of a topic – similar to a comment card.

By integrating digital curation tools and processes into today’s highly advanced social data platforms, users can more quickly define what should be measured and what should be ignored. They can settle in on a concise, realistic set of KPIs. They can align social data more succinctly to business goals. And, most importantly, they can justify the investment in social data by finding unique ‘needles in the haystack’ that often cannot be found via any other type of business intelligence or research platforms.


Upcoming BBI Events!

BBI Community –
We’re excited to announce the dates for Big Boulder 2017, BBI Meetups in September and an amazing event for data-driven digital marketers at Coca-Cola HQ!

Big Boulder 2017
The 6th annual Big Boulder will be held June 1st & 2nd. The only way to ensure your attendance is to join the Big Boulder Initiative. You can register here and tickets will be made available in April. I’ll send out an email with instructions and once the date is closer, please check bigboulderconf.com for updates.

BBI Meetups
We’re happy to co-sponsor a series of Meetups this fall in San Francisco, New York, Washington DC and London. Details are below.

Data: It’s The Real Thing hosted by Coca-Cola and Sponsored by BBI

This conference will provide a holistic perspective on how marketers can utilize data. BBI will be sponsoring the social data presentation and we’re excited to be a part of this amazing event. Some of the tentative session titles/topics are:

  • What’s My Name? A day in the life of data: What data is worth purchasing? So many vendors where does one start?
  • 99 Problems: Programmatic & Direct Advertising: How does the industry toe the line? Am I over or under invested?
  • The Symphony: Are you listening? Making Sense of Social Data
  • Paid in Full: Closing the loop for CPG companies: measuring marketing w/ dollars and sense
  • DMPs and the New World Order: How marketers from various industries are leveraging Data Management Platforms.
  • The Revolution Will Not Be Televised: Where to invest in linear, digital video or addressable?
  • Follow the Leader: Making the most of mobile (targeting, marketing and measurement)
  • A Good Day: Telling Better Stories with Data

The event will be held on November 17th, at The Roberto Goizueta Auditorium, Coca-Cola HQ. The address is 1 Coca-Cola Plaza, Atlanta, GA 30313. Please email me at mike@bbi.org for more information.


Thoughts from Big Boulder

Big Boulder 2016 is a wrap! We are grateful to the speakers, panelists and moderators for sharing their ideas and insights. And we are, of course, grateful to all of you who attended and made this not just a conference, but a community.

Our Big Boulder 2016 emcees, Mark Josephson, CEO of Bitly, and Farida Vis, Director of the Visual Social Media Lab at Sheffield University, shared several overarching themes that reverberated throughout this year’s event:

  • Big Boulder reveals what we don’t know, what we should know, and what we could know.
  • The evolving role of platformsfrom machine learning to algorithms to bots—is fundamentally changing how we think about ourselves as human beings.
  • “It’s the power of us,” said Mark. The biggest problems in the world get solved by networks, not by one person sitting alone in a room. And everyone at Big Boulder is helping to move our industry forward.

“The conference is about what happens on stage and perhaps even more, what happens across the community of attendees off-stage,” said Chris Moody, VP of Data Strategy at Twitter and Chairman of the Board of Big Boulder Initiative. “This room has high concentration of a group of people that can change an industry!”

You can view of all the blog coverage from Day 2 of Big Boulder 2016 below:

As we close the fifth year of Big Boulder, we plan to extend the insights and energy at this year’s event into opportunities to connect year-round.

We invite you to get involved in our Slack community and consider joining BBI as a member of our industry organization.

Thank you for an incredible Big Boulder 2016!



The Future of Bots

This session began by listening to a fascinating conversation between Sam Mandel, the Operating Partner at betaworks, and Chris Messina, the Developer Experience Lead at Uber. The VP and GM Klout and Consumer Data at Klout, Tyler Singletary, moderated this interaction. So how are things really developing in this space? More has changed within the bot world in the last 6 months than in the past 10 years. As process and growth has ramped so up quickly, it only made sense that the last panel of Big Boulder 2016 would be looking into the future of bots and their impact on human interaction.

Bots 3

In the existence of bots, they have had a “science-fiction fascination” behind them which has people interested; it’s now sexy to talk about bots. Messina commented that bots are exciting because there is a shift now of making computing more accessible to a wider range of people. Which makes sense, seeing how the number of consumers on the web only grows every day. And not only on desktops. Messina stated that Mark Zuckerberg estimates that the next generation of web users to come online will primarily be using phones and other mobile devices.

This all brings up several question for the user. Should bots be inside messenger apps at this moment? Should you build it and they will come? Or will the creators and implementers of bots have to also acclimate the users?

Users’ expectations guide these decisions as well. As Messina commented to Mandel, his experience with Poncho, an app that delivers customizable weather forecasts, is that the program does not learn as fast as he’d like it to. Which is to be expected, as there is much “grey area” that is encountered in this new industry, as Mandel puts it.

Sam Mandel went on to explain that the majority of consumers do not fully understand the world of bots or how to use them properly. The act of stepping back, creating simpler processes, and having more direct training is crucial in moving forward in the field. To put it simply, it’s different talking to a bot than it is talking to a person. Bots are just less capable. However, it should be noted that, since most people are now trained in executing Google searches, the Google search engine has now improved in understanding specific and customized requests. The “one-size-fits-all” approach doesn’t cut it anymore now that the dynamic is shifting.

Looking ahead, the future of bots lies with the constant change that the world has experienced in the past 10 years. There will always be room for improvement, for better connections between humans and applications. As users move to a “much more diffuse world,” the tech will be more and more align with how humans interact in the world today. The potential is there, and one can only wait in anticipation to see where it leads them.


Messaging in the World of Bots

When moderator Chris Moody, VP of Data Strategy at Twitter, polled the Big Boulder audience, about 15% of the group had used Kik, a mobile messaging app. Michael Roberts, Head of Chat at Kik, says that 15% is a good show of hands in an audience like Big Boulder. That’s because Kik is used mostly by teens in the United States. In fact, of the 300 million registered Kik users, 40% are U.S. teens. Michael said that high usage is because teens are the first generation of digital- and mobile-native users and naturally know how to interact with bots.


Anonymity vs. Pseudonymity

Kik empowers users to form an identity inside the app. Rather than anonymity, which is meant to strip identity from a user, pseudonymity allows users to form any identity they choose. The average Kik user spends 87 minutes inside the app every dayan amount of time that allows users ample time to develop a persona and express themselves.

Bots are Hot

“Right now there are a lot of trends coming together at the same time, including NLP, AI, and machine learning,” Michael explained. Bots are hot because they aren’t only about those trends, but instead are about trying trends together seamlessly inside of messaging apps.

The popularity of bots makes sense also because it’s easy to reach a digital-native audience. Bots are an interface that digital natives already understand. There’s no learning curve, which allows companies to reach these users easily.

Bots are hot also because they let companies build inside of apps that are already on mobile phones, providing a huge opportunity to reach customers. Bots are another tool in a mobile developer’s toolkit. “The future isn’t putting bots in products,” said Michael. “The future is building better products.”

Beyond One-to-One Conversations

Bots aren’t just a one-to-one conversations between a user and a bot. Far from it. For example, using the “@mention” bot in an app, like the one that exists in Kik, allows a user to pull a tic-tac-toe game into a conversation between friends. It’s not about talking with bots directlyit’s about adding bots into existing conversations.

Games are another opportunity for bots to engage users in a broad way. According to Michael, 40% of all app content in the app store is a game, and 80% of revenue on mobile is through games. Games provide a tremendous platform for bots to move beyond one-to-one conversations and to be a seamless, natural part of the gaming experience.

Retailers with brick and mortar stores can bridge the gap between physical space and digital community using bots. Companies such as Sephora and H&M are using bots to connect with users, even when those users aren’t at a store.

Privacy, Control and Bots

As surfaced in other panels during Big Boulder, bots raise the question of how much messaging to a user is too much. Michael described that at Kik and in Kik’s Bot Shop, a balance of retaining a user by notifying them about activities, but not overly spamming users with too many bots is a careful balance.

Kik also thinks about users in terms of trust, intimacy, and control. The company tailors experiences for users so that users retain privacy and safety.

Measuring Bot Success

Bot messaging is unlike any other app platform, according to Michael. Common app metricslike MAU (Monthly Average Users) or quantity of app downloadsaren’t relevant to bots. Instead, Kik uses chat sessions as a better metric to measure success. Chat sessions reveal how long a user is inside a chat, how active the conversation is, and what other bots users bring into the messaging platform.

The future of bots is likely to feature bots not just as a single, siloed tool but instead as a platform-agnostic way to engage users.



Building Digital Analytics Capabilities in a B2B World

The final Pecha Kucha talk of the conference was delivered by Chuck Hermann, Director of Digital Analytics at Intel, who gave the audience a rundown of what it’s really like to build a Digital Analytics platform and team for a Fortune 50 company. In 2014, Hemann was asked to join the Intel team to begin a new department and transition the company from the B2C to the B2B world. Hemann covered the life cycle of this project over the course of the last two years, addressing three specific focus areas for those who may be undertaking similar projects in the future:

  • “Where did we start and what did we learn?” Two years ago, not only was there no Digital Analytics team to speak of at Intel, but their digital measurement framework was also extremely elementary for what they were trying to accomplish: one based on clicks, but not on attitudes. Internal reports were rarely consumed–most people weren’t even aware they existed. When Hemann arrived and began his work, he immediately hired senior-level talent with a wide range of skills to hit the ground running. Even with a high-caliber team with plenty of experience, he noted that changing a measurement framework is at least a 6-9 month process, and that’s if it’s all done well, start to finish. Another note of importance: what is effective in the B2C space is not always effective–or sometimes ever effective–in the B2B space.
  • “Where are we now and what are we learning?” Hemann maintained that the long-term vision of the team and of the company was not to build a system that would transcend the ages–they wanted to keep in mind the elasticity needed for new tools and new methodologies to be created. This vision was and is critical: without a vision, and without a mission, there is very little starting ground of which to speak. Hemann and his team had to determine what they wanted from their project (to enable Intel to become a best-in-class data-driven global marketing organization), as well as how they would achieve it (deliver relevant and timely insights to stakeholders using future-ready tools). Hemann noted that tools, however, are only ⅓ of the equation for success: without the right people and the right processes, the vision and the mission cannot be realized.
  • “Where are we going and what do we hope to learn?” Once mission and vision are established, benchmarks for success are necessary to determine how far a team has come and how far they have yet to go. Hemann’s team created not just one objective, but three separate objectives that would serve as checkpoints or progressive phases for a roadmap to future success: 1) expand scope, 2) communicate, educate, and deliver insights, and 3) establish a governance framework. Hemann emphasized that without a proper governance framework, no actions will be effective enough to achieve the desired objectives.


Overall, Hemann’s insights from the perspective of a Fortune 50 company were especially valuable to conference-attendees who may be struggling to determine if their own company’s digital analytics journey is headed in the right direction. His final takeaways for attendees were beneficial as general philosophies for anyone inside of the digital space: make collaboration a primary focus, and be patient. Rome was not built in a day, Facebook did not become a behemoth in a year, and building a department from the ground up–particularly when the premise of the department remains uncertain for the future–means to collaborate early, often, and over long periods of time to make it right.