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Companies in social media analysis announced receiving over $190 million in new investments in 2012. Add quiet investments and the value of the year's mergers and acquisitions, and it's real money. Here's a recap of the year's investment activity.

See all of the recent funding headlines on one page: Investments in Social Media Analysis

2012 has been another active year for the buying and selling of companies in social media analysis. As suppliers have taken different approaches to social media data and the market, the transactions reflected different goals. Companies bought each other for technology, products, or market presence—even for their key employees. According to SMA's acquisitions scorecard, 24 companies in social media analysis changed hands this year, up from 20 last year. Here's a recap of the year's deals.

Acquisitions in social media analysis 2012

WPP kicked things off with its acquisition of the China specialist CIC, followed quickly by MediaMiser's technology-motivated pickup of InfoGlutton. Ending the month, SDL closed its acquisition of Alterian, marking the longest string of acquisitions to date (Andiamo Systems to Techrigy to Alterian to SDL).

Dassault Systèmes bought Netvibes for the value of consumer opinion in innovation, and thismoment took over Position2's Brand Monitor product. Connotate acquired Fetch Technologies in the first transaction to point out the fuzzy boundaries of the space this year.

April must be the big shopping season for companies. The Japanese market got a little easier to follow when Hottolink bought Gala Buzz from its parent company. Visible Technologies bought Cymfony from WPP, the first time an acquired startup in the space has been resold. KPMG quietly bought WiseWindow, incorporating its product and team into KPMG's analytics business. Progressive Media Group quietly bought Attentio, but there's been no indication of what they plan to do with it.

Enterprise software companies took multiple trips through the checkout lane. Oracle bought a social media business with Vitrue and Collective Intellect, and added Buddy Media to the business it started with Radian6 last year.

Syncapse bought Clickable to add social and search advertising management to its platform.

Regional holding companies strengthened their company portfolios through acquisitions. In July, News Group International added Report International and KD Paine & Partners to its stable of media monitoring and analysis companies for the Middle East, Africa, and India. In August, Sentia Media made a similar expansion in its Asia-Pacific group with Australia's BuzzNumbers.

Also in August, Facebook played the game when it acqui-hired Threadsy.

HootSuite bought Seesmic and reiterated its commitment to power users and the business market. Lithium Technologies bought Social Dynamx to add customer service capabilities to its suite.

NM Incite bought SocialGuide to link TV ratings and tweets about television. Eptica bought Lingway for its text-analytics technology, and Brand Embassy bought Beepl for its text-analytics technology. A trend?

Unless someone has an announcement to make in the next two weeks, the year ends with Ninestars adding NEWBASE to its product portfolio and gaining European presence in the process.

2013 awaits. What's on your shopping list?

Automation Key to High-Volume Analysis

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This post introduces a new opinion section on SMA. The opinions expressed are those of their authors, and I invite you to share yours, either in the comments or in your own guest post. In the spirit of the great opinion journals, SMA invites an open discussion of topics that matter.
- Nathan Gilliatt

Machine-based sentiment analysis is key to processing large amounts of data
by Mike Marshall

There has been ongoing debate in the text analytics world regarding accuracy of sentiment as it pertains to automated analysis vs. human analysis. At the very least, customers and vendors can agree on the value of sentiment analysis when applied to unstructured text, but deciding how and when to use automated vs. human methods continues to be up for discussion.

Language is a complex thing. We would never argue that. In fact, sarcasm, irony and sometimes even just simple misspellings can confuse even the most complex automated sentiment systems, leading it to apply the incorrect sentiment to a piece of text. This is the meat and drink of the proponents of the theory that all sentiment analysis should be done by humans, who will gleefully point to the fact that the machine got the sentiment of a document wrong. However, what they are less likely to point out is the fact that humans get it wrong as well and that unlike an automated system, are affected by external factors, such as going out for a few drinks the night before, or having a disagreement with a co-worker. In fact, anecdotal evidence suggests that two human analysts will only agree with each other approximately 80 percent of the time, so one of them must be wrong (if not both), and this is very close to the accuracy rates that the best machine systems will achieve when applied to a large corpus of documents.

The fact that a machine-based sentiment system can process a large document corpus relatively quickly (three or more documents a second per processor) is a big factor in its appeal. It's also important to realize that for many applications—including online search-based web sites—it's the overall accuracy of a sentiment engine across hundreds or thousands of documents that really matters. Another example of this is can found in financial services where sentiment for an individual stock can be measured to help predict the trading range of that stock; the sentiment of an individual story is unimportant, it's how that stock is trending across all the news that actually matters. In these cases, a machine-based system is better than humans because it can scale up to very large volumes of information.

So, what's the moral of the story? As in most things it's somewhere in the middle. The future is probably a combination of human- and machine-based sentiment. Humans bring something very important to the table that machines are never going to have and that is domain-specific knowledge and experience. For instance, in the world of pharmaceuticals, the sentence "the drug killed the tumor dead" is actually a pretty positive thing. A system that enables the human analysts to import that knowledge into the machine and then lets the machine take over the drudgery of actually processing the documents is surely the best of both worlds.

Mike Marshall is CTO of Lexalytics.

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