Market Strategies International recently released the first edition of what it says will be an annual Social Media Brand Index, a measure for brands both of consumer-generated social media about them and of their own sponsored content. The Index takes into account four components. Volume, or the amount of buzz about a brand online, is one of them — and its most highly weighted component, too. The others take their cue from what we might call more meaning-related measures, sentiment analytics and semantic markup among them.

For example, there’s net Sentiment, which Market Strategies says represents the ratio of positive to negative sentiments expressed about a brand based on automated natural language processing of the content of posts, comments and mentions. Another component, Positive Emotions, seems to flow from that measure, representing the number of content items that are identified as having the warm fuzzies about them, again based on automated coding of content.

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SemTechBiz is Less Than 2 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !

Hojoki, the cloud productivity-app aggregator with semantic tech underpinnings that The Semantic Web Blog first discussed here, is going mobile. The company’s launching the take-along version of the app, which delivers a single newsfeed of users’ cloud-connected work, for both Android and iOS platforms at The Next Web Conference’s Startup Rally event.

In the coming weeks, the mobile version will add to the newsfeed features including collaboration and push notifications, says CEO and co-founder Martin Böhringer.

As far as collaboration goes, the company is announcing in conjunction with its mobile news the addition of new social features to make that process easier. It wants to advance the cause of helping users leverage what it calls the much- overlooked Work Graph. “Our mission now is: discover the Work Graph,” says Böhringer. The Work Graph, he explains, consists of the people you’re working with, and Hojoki already know most of them if you’ve connected it to some productivity apps.

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What’s on the markup menu for the restaurant industry?

Among the schema.org tags for marking up web pages is one for restaurants, which includes item properties for priceRange, servesCuisine, place, and menu, among others. Restaurants that use the markup language to structure their data are promised search engine optimization (SEO) benefits when hungry consumers want to see what’s on the menu at moderately-priced nearby Italian eateries, for example. They might also or alternately use the GoodRelations ontology for e-commerce to better accommodate search engines, as well as mobile and desktop apps, with service details of hours, payment options, and daily menus that are accessible in up to 50 languages.

OpenMenu has a value proposition around structured data for restaurant owners, too: Providing increased exposure to Internet, mobile and web apps, via what it aims to be a global and open standard for storing, sharing and using their menus over the Internet. The technical details are described at its OpenMenu.org site. Initially launched in 2010, it recently updated the format to Version 1.6 and currently counts about 75,000 menus as part of its landscape – 5,000 of them actively maintained and growing at a couple of thousand a week, according to CEO and founder Chris Hanscom.

Third-party developers can harness the data too, to build applications that interact with menus, like OpenMenu Search, a way for a search engine to drill down through a restaurant’s information to the menu and menu items.

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The latest version of the StreamGlider iPad news reader app for providing consumers with topic-oriented streams of information debuted this week. It brought with it the capability to limit hashtag or keyword searches in a Twitter, YouTube, or Flickr frame to a local area and turn on geo-awareness at the user’s request. But the bigger and more semantic event will be StreamGlider’s upcoming move to the enterprise, with the consumer app serving as a showcase to those potential customers.

StreamGlider CEO Bill McDaniel – also CEO of SemantiStar, which developed the application that The Semantic Web Blog first covered here and here – says to expect in the enterprise edition a very interesting semantic search/semantic relations engine in the background for correlating up to three data sets of semi-structured, unstructured and structured data. The company already is working with one client on a specific application of the generic technology for its custom needs, and talking to a second customer about a pilot around the idea.

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Just a little over a year ago The Semantic Web Blog introduced our readers to Gravity in this article. The project, spearheaded by former MySpace execs, is focused on building the Interest Graph. The team’s been pretty quiet about development efforts since that time — until just this month, when it announced Gravity Labs to let the public in on a little more about its underlying Interest Graph infrastructure and to showcase the platform. It also announced that it was open-sourcing some of the “plumbing” code it came up with during development, while understandably keeping its core IT, ontology and algorithms under wraps.

The announcement noted that the internally-named Gravity Interest Service for personalizing content at scale, in real-time, went live at production-scale 6 months ago. So far the technology has created over 400 million user interest graphs; served over 13 million pieces of personalized content per day; personalized the daily Internet experience of tens of millions of users per month; and processed over 25 million inbound interest signals per day, the company says. It expects that at this rate, that in under six months it will be handling 10X all of these numbers.

The Semantic Web Blog once again caught up with Gravity CTO Jim Benedetto to talk some more about the Interest Graph, a term he acknowledges gets thrown around quite a bit these days, with a lot of web sites claiming they’ve got the goods. But, he says, “what they effectively are saying is that buried deep within the data of our logs or deep in the data of how our users interact with our site, we know there are interest indicators there. But a lot of them are not doing much with their data.” Interest Graphs, he says, aren’t owned, but interest data resides in individual places and across the web at large — and they need the Gravity platform to help unlock that to create dynamic and personalized experiences for users, Benedetto says.

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Semantic startup PeerIndex has raised $3 million in Series A funding to help build its social influence marketing platform. According to Krystal Peak of VatorNews, “PeerIndex, much like Klout, claims to measure just how influential people are online by using algorithms to see how may people read and re-tweet their Twitter activity or respond to Facebook status updates or connect with them on Foursquare and other services. But consumers around the globe have been critical of just how these influence rates are calculated and whether influence is certain categories is weighed more heavily than others.” Read more

Karen Hanna recently posed the question, can Twitter predict the President? She explained, “Some data analysts are looking at political sentiment in social media data to make predictions around the presidential campaigns. Attensity looked at 800,000 Tweets from February 25 through March 2 and measured ‘positive sentiment and share of voice for each candidate.’ Attensity determined that Romney would win seven states, Gingrich would win Georgia, Paul would win Alaska, and Santorum would take Vermont. Attensity was asked by USA Today to analyze Twitter data to predict how voting would go on Super Tuesday. Attensity is a social analytics company based in Palo Alto. Like other social media analytics companies, it is interested in how text analysis techniques might be applied to data collected from social media to enhance market research capabilities.” Read more

Russia’s leading search engine Yandex – which is collaborating with U.S. search engine giants in implementing schema.org and which last week partnered with Twitter to post tweets in real-time in search results – has made another deal this week: It’s working with Topsy Labs to enable social search.

Real-time search and analytics provider Topsy’s indexing and live-ranking will help Yandex search in Russia and Turkey identify and extract fresh and relevant results from social media sources. Vipul Prakash, Topsy’s co-founder and Chief Technology Officer, says Topsy’s corpus consists of about 100 billion tweets, and the page links and media referred to in them, all time-stamped and authorship-explicit. It does some amount of synthetic tagging to extract the topic from the tweet to make the topic searchable, as well as performs classification of content, where there’s more text to play with, for links referenced in tweets. It understands that the author is distinct from what is being discussed and who is referring to whom in postings, which feed into its graph of influence that ranks links in search results based on the influence of people talking about those links. That includes a global rank of a user independent of topic and terms and also keyword-level ranks based on what was in a tweet when they got attention for it.

Because it has such histories of people to extract from that a robust understanding of their network credibility, including how they’ve received attention from others in the past, Topsy does a really good job of getting rid of spam, Prakash says. That’s a particularly useful capability to bring to Yandex to weed out suspicious social tweets in advance of the controversial Russian presidential elections getting underway this weekend, as reports have noted that fake Twitter accounts have been created to drown out opposition voices by flooding Twitter’s hashtag service function. “In Russia there is a lot of precedent for political activism like that,” he says. “If something points out a problem with a candidate, they will have people start spamming it so you can’t actually find the real piece of information.”

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Twitter has sold its old tweets to DataSift, a company that plans to analyze the tweets for marketing purposes. DataSift is the first company to get access to these tweets which go back two years. According to one article, DataSift has “launched a product called DataSift Historics, which lets companies extract insights and trends that relate to brands, businesses, financial markets, news and public opinion, a rep says. DataSift will analyze public tweets, not private ones. If you delete a tweet, it’s deleted from DataSift’s archives.” Read more

Yandex, the up-and-coming Russian search engine has struck a deal with Twitter allowing Yandex to post new tweets in search results in real-time. According to the article, “Twitter will give Yandex access to its so-called firehose of all public tweets, the two companies said on Tuesday, in an agreement similar to the one the social short-messaging site has with Microsoft’s search engine, Bing.” Twitter’s director of development April Underwood stated, “We wanted to make sure that Twitter content can be where Twitter users are already going… Discovery through search is so important.” Read more