Category Archives: Language Technology

Posts about language technology.

Case Study: Text Analytics against Fake News

Everybody has heard about fake news. Fake news is a neologism that can be formally defined as a type of yellow journalism or propaganda that consists of deliberate disinformation or hoaxes spread via traditional print and broadcast news media or online social media. It is also commonly used to refer to fabricated or junk news, with no basis in fact, but presented as being factually accurate.

The reason for putting someone’s efforts in creating fake news is mainly to cause financial, political or reputational damage to people, companies or organizations, using sensationalist, dishonest, or outright fabricated headlines to increase readership and dissemination among readers using viralization. In addition, clickbait stories, a special type of fake news, earn direct advertising revenue from this activity.

Continue reading


How Artificial Intelligence makes RPA smarter: two use cases

RPA-automation-computer-robot-tools and statistics

Artificial Intelligence and RPA

Many organizations could be gaining huge operational efficiencies if they combined Artificial Intelligence and RPA (Robotic Process Automation).

In a previous post (The leading role of Natural Language Processing in Robotic Process Automation) we introduced the subject of NLP in RPA. In this post, we are seeing two use cases where Natural Language Processing (also known as Text Analytics) integrated with RPA/BPM software suites, is mature enough to solve typical insight extraction problems, conveniently and cost-effectively.

Continue reading


We The Humans: Artificial Intelligence for social good

MeaningCloud partners with the think tank “We the Humans“, sponsoring the challenge “Artificial Intelligence for social good”.

The mission of “We the Humans” consists in:

  • Encouraging the social debate about the correct use and development of Artificial Intelligence.
  • Bringing these concerns to the public agenda.
  • Supporting organizations in the development and adoption of an ethical AI.


We The Humans Think Tank
Continue reading


Case study on the voice of the patient for the Pharma industry

Pharmaceutical companies are extending their Voice of the Patient projects to include social media: comments on web forums, surveys, Twitter, and more.

The goal of the proof of concept ordered by one particular pharmaceutical company in Spain was to: ” Collect and analyze the voice of the patient, both quantitatively and qualitatively, from the channels where it is expressed”, including social networks like web forums, Facebook, Twitter, and other systems.

For the pharma industry, it is essential to listen and understand the feedback that their current and potential customers communicate through various means and touchpoints.

Web forums, for instance, gather millions of posts, and function as a meeting point for patients where support, experiences, and wisdom are shared with peers, family members, and friends.

Continue reading


Web scraping and text analytics

Text analytics projects are often dependent on Internet-based public sources such as the World Wide Web. These projects usually begin by extracting data from a variety of websites. We call this process “web scraping” (or “web harvesting”). While users can handle web scraping manually, the term often refers to automated methods executed utilizing a web crawler.

Examples of projects that offer a valuable wealth of information include customer experience (in the same way as patient experience or employee experience), dynamic pricing and revenue optimization, competitor monitoring, or compliance checking. Continue reading


People Analytics: MeaningCloud book on Amazon!

People Analytics. Data and Text Analytics for Human Resources

People Analytics. Data and Text Analytics for Human Resources. This MeaningCloud book is available on Amazon.

In People Analytics, and in this book, we use the evidence that the data provides to respond to several questions:

  • Which candidate will be high-performing, effective, loyal, and aligned with the corporate culture?
  • How can we measure the economic impact of a training program?
  • How can I segment the workforce to make their actions more effective?
  • Which people are considering leaving the organization?
  • What net benefit will employees contribute throughout time in a particular position?
  • How does employee commitment affect productivity and economic outcomes?
  • How can I design a study that is statistically and mathematically valid?

Continue reading


Contact center: 6 ways to leverage text and speech analytics

Contact center. Ilustration

At contact centers, text analytics technology provides an unprecedented opportunity to convert customer interactions into business opportunities. We can improve customer experience, boost sales, reduce customer churn and streamline the efficiency of the processes.

Continue reading


Text analytics explained: MeaningCloud in Italian

In previous posts we spoke about text analysis performed in French and Portuguese. Today we’re wrapping up this linguistics series by discussing the analyses that can be done with Italian texts.

Italian is spoken in several European countries such as Italy, San Marino and Switzerland, totaling almost 70 million speakers. As Italians have migrated all over the world, its language is also present on the other side of the pond. In South America, for instance, it is the second most spoken language in Argentina. In the US, even though it is not an officially spoken language, many of its citizens are of Italian descendent and thus speak the language at home. We wanted to include such a widely spread language in our Standard Languages Pack.

Hello in many languages

Similarly to our previous posts, we are going to explain, in a linguistically-inclined way, what Text Analytics is and which functionalities MeaningCloud provides in Italian.

Continue reading


TASS 2018: Fostering Research on Semantic Analysis in Spanish

MeaningCloud and University of Jaen have been the organizers of TASS, the Workshop on Semantic Analysis in Spanish language at SEPLN (International Conference of the Spanish Society for Natural Language Processing), again in 2018.

TASS logo

During the years, the research has extended to other tasks related to the processing of the semantics of texts that attempt to further improve natural language understanding systems. Apart from sentiment analysis, other tasks attracting the interest of the research community are stance classification, negation handling, rumor identification, fake news identification, open information extraction, argumentation mining, classification of semantic relations, and question answering of non-factoid questions, to name a few.

TASS 2018 was the 7th event of the series and was held in conjunction with the 34rd International Conference of the Spanish Society for Natural Language Processing, in Seville (Spain), on September 18th, 2018. Four research tasks were proposed. MeaningCloud sponsored this edition with prizes for the best systems in each of the tasks. A comprehensive description paper is (to be) published in Procesamiento del Lenguaje Natural journal, vol 62: TASS 2018: The Strength of Deep Learning in Language Understanding Tasks.

Continue reading


Pharmacovigilance: Monitoring the Voice of the Patient

Pharmacovigilance: Voice of the Patient

For the pharmaceutical industry, it is essential to listen and understand the feedback that their current and potential patients communicate through all sorts of channels and touchpoints.

Although there is a protocol that requires any identified Adverse Drug Reactions (ADRs) to be disclosed to the authorities, only 5–20% of them are reported. Fortunately, discussions regarding drugs, symptoms, conditions, and diseases can be analyzed to learn more about said branches of pharmaceutics. Artificial Intelligence significantly contributes in monitoring adverse episodes and understanding their impact in every phase of development.

Patient narratives of medicines and their adverse effects on social media represent an extra data source for drug safety monitoring.

At MeaningCloud, we have developed a platform to automate the process of monitoring ADRs on social media.

Continue reading