Big Data In Small Pieces – Social Media & Facebook Graph Search
Big data drove $2b million of global IT spending in 2012. What’s more – a massive 90% (source IBM) of the data in the world has been produced over the last two years through digital, social media and location based data.
Facebook’s launch of Graph Search last week signifies the fusion of Big Data and social networking. Facebook Graph Search allows you to search and be presented with results based on your personal ‘social graph’ (likes and connections). The information you are served from Facebook’s big data set is relevant to what your friends and connections like.
Much has been written over the last few days on Facebook and Graph Search, so today I have taken a slightly different angle to focus on the big data and social graph relationship – piece by piece.
The Big Data Challenge
Making sense of Big Data has always been a challenge for marketers. The fragmentation of media in many ways made this more difficult and the explosion of social media added more data and more layers to the Big Data marketing equation.
With 51 million websites added last year and 4 billion pieces of content being shared each day utilizing personal social graph data from Facebook and other social data from Google, location data and database (CRM) data allows you to market and take advantage of personalization, preference and inference through persona based marketing techniques.
Big Data – Small Pieces
An easier way to look at the growth of Big data and the relationship from digital, search, to user based social graphing is to break it down to show how the growth of search, social, local, video and mobile content influence social graph search.
Facebook’s launch of graph search shows how big data can be utilized and broken down into pieces/layers.
Big Data represents large volumes of information. Over 2.7 Zetabytes of digital data exist today and the IDC estimates that by 2020, business transactions on the Internet will reach 450 billion per day.
This data comes in multiple formats such as structured from databases around the world, unstructured data from raw format and web applications, and semi-structured data (Facebook Graph Search) from user generated content, sharing, social media and location type data.
Search and Social and Big Data
Big data is the glue that binds the digital marketing ecosystem. It is not new but has been widely talked about in technology and digital (advertising and display) disciplines for a decade, more so than is search and social circles until Facebook introduced us to the Open Graph at F8 in 2010.
The content and data produced from building web pages and content search marketing and the data produced from social media activity have driven the growth of Big Data. According to IBM 90% of global data has been produced over the last two years. The adoption of mobile devices combined with this social and digital media content and location data are the prime drivers of data growth.
Search, Social and Knowledge Graphs– Facebook and Google
Breaking down Big Data and utilizing the huge amounts of content and social media data has fostered rapid innovation in the social graph space. Just like the search space initially produced the link graph. Adding social layers to big data allows Facebook to compete indirectly with search giant Google.
The are several innovations in this space based on Interest, Preference, and location. Back in 2011 Bob Triola provides more insight into this in his article The Business Of Social Graphs
- Interest Graphs – Facebook, Twitter, Google +, Quora
- Taste Graphs – Hunch
- Location Graphs – Foursquare Venue Project
- Health Graphs – Runkeeper
- Yelp – Social and location
- Pandora – Social, interest, tastes and music
- GetGlue – Social, interest, music, movies, tv
- Pinterest – Social, image, taste/preference
Whilst Google continues to build its knowledge graph through the likes of Google+ (pardon the pun) Facebook has a distinct advantage with 3.3 billion pieces of content being shared on Facebook each month.
Facebook Graph Search
Facebook’s Graph Search is basically personal big data. It’s a search engine based on your data and your network data – connections and likes. It is not aimed to be a Google killer per se. It has taken a layer of big data and built a preference engine around this that represents a new era in the development and relationship between search and social.
Graph Search blends local, social and content data for individuals and, eventually for businesses. Danny Sullivan from Search Engine Land wrote, probably the first piece on the topic, about the differences between Facebook Graph Search and Google Search
Another difference is the layers of searching or refinement that Facebook Search offers compared to Google. For example, a Google search can show you restaurants in San Francisco, a pretty much single dimensional view.
A Facebook search can show you restaurants in San Francisco liked by your friends. Or further, those liked by your friends who actually live in San Francisco, as opposed to those who live elsewhere. Or those liked by your single friends, your straight friends, your gay friends, your friends who work for a particular company….
Below are a few key points from me to consider and some links to key articles on the topic
- Facebook Graph Search is not a Google Killer
It has potential to makes a dent in Google’s web dominance. It’s partnership and the relationship will Bing will become ever more interesting
- What happens if Facebook adoption has reached a saturation point?
Facebook’s UK users dropped by 600,000 and 1.4 million fewer Americans used their Facebook accounts in December. Seasonality aside this may be an issue
- Facebook Graph Search poses more of a threat to local search sites than Google
As mentioned earlier in the post (the small pieces of big data breakdown) location data plays a large part in Graph Search and it will be interesting to see how this affects local search websites and listings and how Facebook encourages more people to use check-in
- Limited Data and Privacy – The catch 22
Security and privacy of data has always been an issue online. However, as we move from talking about big data to social data consumer become more aware of the issues that this can cause.
Facebook’s decision not to compete directly with Google search limits the amount of information available but it does make you personal information more available for others – friends of friends and likes.
- It is too early to predict success
Success depends on your Facebook audience and your personal preference. It is important to look at the quality of your friends and connections and how much you ,and they, like and share. Can Facebook convince consumers of the credibility of results? Success depends upon the credibility of your ‘friends’. Once we have a roll out to business success and credibility will rely on how well business optimize their business pages
Big Data is growing thanks to digital, social and location based data. Social and interest graphs represent both the creation and filtering of social media Big Data. As more layers are added to the social web the more interest people take into privacy and security as big data, and their data, is put in front of them.
The future lies in the quality of connections and the quality of data and if you are interested