Posts Tagged ‘movies’

Oscar Picks With The Help of Semantic and Sentiment Analytics Technology

Sunday night’s the big stroll down the red carpet for Hollywood’s elite — for the 85th time. But no need to wait until then to have some fun with old Oscar.

Some services with semantics and sentiment analytics in their genes have already begun. Here are a few examples:

Jinni, the semantic movie and TV Taste engine, has created a detail-filled graphic, based on analysis and cross-referencing it did according to its own Jinni Entertainment Genome (see its blog post here for a look at the entire graphic and more info on its creation):

























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Moviegoer Social Sentiment: Big Data Analysis For Big Business

Like lots of other families over the recent Thanksgiving weekend, we made our way to the movies. Our choice: Life of Pi. We’d highly recommend it, and according to the IBM Social Sentiment Index, as applied to Moviegoer Social Sentiment over the holiday weekend, so too would a lot of other folks. It earned a 90 percent positive rating.

IBM has engaged in the social sentiment index pursuit in some other endeavors – using its advanced analytics and natural language processing technologies to analyze large volumes of social media data, it had another recent take on Black Friday, for example. It tallied up that shoppers expressed positive consumer sentiment on promotions, shipping and convenience as well as the retailers themselves at a three to one ratio (see our story here for other takes on semantic tech weighing in on the holiday shopping season).

It’s also applied its social media analysis smarts to studying births of trends (cycle chic is on the rise), and which tennis player was on the hearts and minds of the crowd at the U.S. Open (Novak Djokovic and Laura Robson winning the love, with positive sentiment scores at 90 percent or better).

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Finding Better Movies with Nanocrowd

Rafe Needleman recently reviewed Nanocrowd, a movie recommendation engine that uses semantic analysis to provide users with optimal film suggestions. Needleman writes, “Rather than collect your viewing history and asking you to rank what you’ve seen (as Netflix and Tivo do), Nanocrowd lets you start with one movie and then it tries to tease out what it is about that film that you’re liking right now. Then it finds more like that.” Read more

Jinni Offers Taste & Mood Based Discovery Engine for Film & TV

A recent article reports, “mgMEDIA, developers of multi-device digital content distribution platform Open4Content and Jinni, innovators of the only taste-and-mood based discovery engine for movies and TV shows, today announced a new strategic partnership to deliver a fun, intuitive and highly accurate Jinni semantic discovery experience. The Jinni discovery engine will be built in to the core of mgMEDIA’s over-the-top platform, Open4Content. Users will enjoy finding and viewing high-quality entertainment that suits their personal tastes and moods anytime, anywhere.” Read more

AOL Takes On Movie Sentiment (And Justin Bieber Too?)

We reported a couple of months back about how AOL’s purchase of the Huffington Post delivered some more semantic technology to its doorstep. But that’s not the only semantically-related project underway there: Amit Moran, R&D Manager at the AOL Relegence team, is working on a movie sentiment ranking project using Twitter and other social media data. It should see the light of day in the near future on one of its properties.

“We are developing a general infrastructure for sentiment analysis that deals with finding out what people think of entities in a content stream,” Moran told attendees at the recent Sentiment Analysis Symposium in New York City. The use cases for sentiment analytics are wide – what do you think of a restaurant, or a politician, for that matter  – so domain specificity becomes important in its actual application. AOL went with movies as a first option – not a surprising choice given its ownership of sites like Moviefone.

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Creating Social Apps with Graph API

Facebook’s developer blog recently shared a useful example of how their Graph API can be used to create a sample app that “searches and presents an ordered list of the movies most liked amongst a user and her friends.” According to a related blog post, “At Facebook’s core is the social graph; people and the connections they have to everything they care about. The Graph API presents a simple, consistent view of the Facebook social graph, uniformly representing objects in the graph (e.g., people, photos, events, and pages) and the connections between them (e.g., friend relationships, shared content, and photo tags).” Read more

Semantic Movie, TV “Taste Engine” Jinni Enjoys New Funding, Plans Added Services, and Explains Why It Can Be More Helpful Than Facebook’s Like Button

2010 ended on a down note for VC funds. Word came this week that 2010 represented the fourth consecutive year of declines and the slowest annual period for venture capital fundraising since 2003, according to Thomson Reuters and the National Venture Capital Association (NVCA).

The silver lining, the NVCA said, is that downsizing of the venture industry has positive implications for investors and entrepreneurs.  “An agile venture capital model likely translates into more capital efficient and fewer duplicative deals in the IT arena,” said its president, Mark Heesen in a release, adding, “The most innovative and efficient companies will continue to be funded by the venture community.”

That must be happy news for semantic web movie and TV “taste engine” Jinni. 2011 started out on a good note for the site, with its announcement that it closed a series B funding round for $5 million. The round was led by two strategic investors: Belgacom – Belgium’s leading telco – and an undisclosed Tier-1 connected-TV manufacturer. Jinni’s service enables Belgacom to offer its customers personalized movie recommendations and discovery, on TV, mobile and web platforms. Venture capital firm DFJ Tamir Fishman Ventures (which previously led Jinni’s Round A funding) also participated.

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