Category Archives: Language Technology

Posts about language technology.

Analyzig audience and opinion on live events for Social TV

By the end of June, we took part in the TVX 2014 international conference on interactive experiences for television and online video with a demo entitled “Numbat – Tracking Buzz and Sentiment for Second Screens”. On it we showed our work and expertise on social media analytics applied to television and live events, combining semantic analysis technologies and real-time data processing to get metrics on social audience and opinions about each feature of the live program or event.

Social TV is not only a continuously growing area, but also a thoroughly mature one, with dozens of companies interested in user interaction and social marketing. Social media are giving particular importance to this interaction between users and TV broadcasts. To realize how far the social conversation about international events goes, you could take a look at Twitter’s recap on FIFA World Cup 2014 group stage.

cristianoDuring the conference we could see the ways industry and researchers are taking to make their point on Social and Interactive TV. For example, second screen applications allow viewers to have a deeper understanding on what they are watching, providing additional information related to the broadcast (usually ad hoc and synchronized for a better user experience) or through automatic trends discovery. Other approaches try to help users finding the right TV programs by studying their habits and behaviors when watching television.

For our demo, we chose to visualize two World Cup matches being played at the same time: United States – Germany and Portugal – Ghana.

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Use MeaningCloud API with the GATE plug-in

In our attempt to make MeaningCloud API the easiest way to use semantics in your application, today we are proud to present our latest development, a MeaningCloud plug-in for GATE.

GATE (General Architecture for Text Engineering) is an open-source workbench for text engineering that makes use of any kind of language processing component, from document crawling to search, and intelligent semantic annotations in particular.

Benefits for GATE and MeaningCloud API users

The plug-in provides GATE users a new set of multilingual functionalities, from parsing to entity extraction and sentiment analysis. For MeaningCloud users it would mean an easier and quicker method to prototype full applications including crawling, post-processing or indexing on annotated documents.  Besides, if you’re familiar with JAPE rules, it would enable to post-process, mix and match annotations from different processing resources for more complex pipelines. Finally, GATE is ideal for sharing and evaluating pipelines between team members, which increases productivity and produces more accurate results.

Sentiment Analysis tool for your brand in 10 minutes!

Have you ever tried to understand the buzz around your brand in social networks? Simple metrics about the amount of friends or followers may matter, but what are they are actually saying? How do you extract insights from all those comments? At MeaningCloud, we are planning a series of tutorials to show you how you could use text analytics monitor your brand’s health.

Today, we will talk about the fanciest feature: Sentiment Analysis. We will build a simple tool using Python to measure the sentiment about a brand in Twitter. The key ingredient is MeaningCloud Media Analysis API which will help to detect the sentiment in a tweet. We will also use Twitter Search API to retrieve tweets and the library matplotlib to chart the results.

Brand monitoring

Listening to what customers say on social networks about brands and competitors has become paramount for every kind of enterprise. Whether your purpose is marketing, product research or public relations, the understanding of sentiment, the perception and the topics related to your brand would provide you valuable insights.  This is the purpose of MeaningCloud Media Analysis API, make easier the extraction of these insights from the myriad of comments that are potentially talking about a brand. This tutorial will guide you through the process of building an application that listens to Twitter for your brand keywords and extract the related sentiment.
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Semantic Publishing: a Case Study for the Media Industry

Semantic Publishing at Unidad Editorial: a Client Case Study in the Media Industry 

Last year, the Spanish media group Unidad Editorial deployed a new CMS developed in-house for its integrated newsroom. Unidad Editorial is a subsidiary of the Italian RCS MediaGroup, and publishes some of the newspapers and magazines with highest circulation in Spain, besides owning nation-wide radio stations and a license of DTTV incorporating four TV channels.

Newsroom El Mundo

Newsroom El Mundo

When a journalist adds a piece of news to the system, its content has to be tagged, which constitutes one of the first steps in a workflow that will end with the delivery of this item in different formats, through different channels (print, web, tablet and mobile apps) and for different mastheads. After evaluation of different provider’s solutions in the previous months, the company then decided that semantic tagging would be done through Daedalus’ text analytics technology. Semantic publishing included, in this case, the identification (with disambiguation) of named entities (people, places, organizations, etc.), time and money expressions, concepts, classification according to the IPTC scheme (an international standard for the media industry, with around 1400 classes organized in three levels), sentiment analysis, etc.

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Our new Semantic Publishing API is now available in MeaningCloud

This API allows you to produce and publish more valuable contents, more quickly and at lower costs

UPDATE: this API has been discontinued. Use instead our Solution for Semantic Publishing, featuring APIs like Topics Extraction, Text Classification and Automatic Summarization.

At MeaningCloud we keep developing our roadmap and offering new vertical APIs, optimized for different industries and applications. We are pleased to announce that our Semantic Publishing solutions include a new API, designed especially for media, publishers and content providers in general.

It is a logical step for us, since at MeaningCloud we have been collaborating for years with the most significant enterprises in these industries (PRISA, Unidad Editorial, Vocento, RTVE, lainformacion.com, etc.) and this is one of the markets where we are detecting more demand and where our solutions are gaining more traction.

The Semantic Publishing API incorporates the know-how we have been developing when working with these large companies and packages it in the form of semantic resources, process pipelines and specific configurations for the most common applications and scenarios of this industry: archive management, content generation, customization of information products, etc.

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Textalytics sponsors the Sentiment Analysis Symposium

Next March 5-6, New York will host a new edition of the Sentiment Analysis Symposium. This is the seventh event of a series organized by industry expert Seth Grimes since year 2010 in San Francisco and NYC.

This is a unique conference in several aspects. First, it is designed specifically to serve the community of professionals interested in Human Analytics and its business application. Second, its audience is integrated by a mix of experts, strategists, practitioners, researchers, and solution providers, which makes a perfect breeding ground for discussion and exchange of points of view. Third, it is designed by just one person (not by a committee), a guarantee of consistency. Being an expert in the consultancy business, Seth Grimes achieves an excellent balance of presentations covering from technology to business application. I attended the New York 2012 edition, where I gave an enlightening talk, and I can tell that the experience was really enriching.

Sentiment Analysis Symposium 2014

Do not be misled by the title: do not interpret “Sentiment Analysis” in a narrow sense. The conference is about discovering business value in opinions, emotions, and attitudes in social media, news, and enterprise feedback. Moreover, the scope is not limited to text sources: speech and image are terms of the equation too.

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Recognizing entities in a text: not as easy as you might think!

Entities recognition: the engineering problem

As in every engineering endeavor, when you face the problem of automating the identification of entities (proper names: people, places, organizations, etc.) mentioned in a particular text, you should look for the right balance between quality (in terms of precision and recall) and cost from the perspective of your goals. You may be tempted to compile a simple list of such entities and apply simple but straightforward pattern matching techniques to identify a predefined set of entities appearing “literally” in a particular piece of news, in a tweet or in a (transcribed) phone call. If this solution is enough for your purposes (you can achieve high precision at the cost of a low recall), it is clear that quality was not among your priorities. However… What if you can add a bit of excellence to your solution without technological burden for… free? If you are interested in this proposition, skip the following detailed technological discussion and go directly to the final section by clicking here.

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MeaningCloud – Meaning as a Service: our new SaaS offering

A few weeks ago we were talking on here about how Daedalus (now called MeaningCloud) has explored various API-based business models for marketing its semantic technologies. Our perception was that basic language features are hard to use for many developers —not experts in these technologies— and require them to build solutions through a process of trial and error, in a do-it-yourself fashion, which is slow and inefficient.

Our vision was to offer the market APIs with a more plug-and-play philosophy, which provide a functionality closer to the business, a faster learning curve and, as a result, an increased productivity. That vision has crystallized in our product Textalytics and today we can say that it is now available.

Textalytics is the easiest way to embed semantics into your applications

Textalytics (now called “MeaningCloud”) is a SaaS offering that provides a high-level multilingual semantic processing functionality to those developers / integrators who want to develop semantic solutions in an effective, quick and cheap way. Compared with other semantic offerings in service mode, MeaningCloud offers several APIs, each with a specific functionality which is close to an application domain, and SDKs, plug-ins, etc. that make its learning and use much easier, reducing the effort required to obtain results and time-to-market.

Textalytics - Meaning as a Service

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