Category Archives: MeaningCloud

This category groups the different aspects of MeaningCloud we talk about in the blog.

Accuracy measures in Sentiment Analysis: the Precision of MeaningCloud’s Technology

Accuracy Measures of Commercial Sentiment Analysis APIs

Our clients frequently ask, “what’s the precision of MeaningCloud technology?” How does it compare with other commercial competitors and with state-of-the-art technology? And they demand precise numbers.

That’s not an easy question to answer. Even when there are milliards of research studies on this issue. For the sake of simplicity, let’s concentrate on the well-studied scenario of accuracy measures in Sentiment Analysis. Continue reading


New Excel 365 add-in for Text Analytics!

Our new Excel 365 add-in has finally arrived!

Excel is the preferred tool for many MeaningCloud users. They access MeaningCloud APIs directly from Excel with our add-in. In the last months, we have received a lot of inquiries about Mac support. So, we partnered with Microsoft to build a new multiplatform version.

 

Installation

Installing it is a breeze on all platforms. The new add-in is available in Microsoft AppSource:

https://appsource.microsoft.com/en-us/product/office/WA200002421

Click on Get it Now and follow the instructions.

 

Configuration

You only need your API key to use MeaningCloud. Paste it in the License Key field and you’re ready to start analyzing.

Don’t have one? Create an account for free – no payment method required.

Configuring the MeaningCloud add-in

 

Usage

You can use the APIs directly from the ribbon:

MeaningCloud add-in ribbon

The user interface page describes the different buttons. Paste your texts in the spreadsheet, select the tool in the ribbon, review the parameters and click in Analyze:
Sentiment analysis with MeaningCloud
Take a look at the documentation for more information about add-in usage.

 

But I don’t use Office 365!

No worries. If you use another Excel version, we still offer the previous add-in version. If you don’t use Microsoft Excel at all, you can use our Google Spreadsheets add-on.

 

Questions?

If you have any questions or issues, we will be glad to hear from you. Drop us a line at support@meaningcloud.com and tell us about your experience.

Language Technology vs. Disinformation

Reuters Institute Digital News Report 2020

Following the 2016 US presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. Research from Oxford University’s Reuters Institute for the Study of Journalism has found a long and steady decline in trust in traditional media. (See Reuters Institute Digital News Report 2020). This declining trust coincides with the uprise of social media as a main source of information. In 2020, social media was a source of news for 48 percent of the public, up from 27 percent in 2013, according to the Reuters Institute.

Continue reading


IAB Taxonomy Level 3 now available in our Deep Categorization API

IAB - Interactive Advertising BureauDigital marketing is becoming a fundamental pillar, by leaps and bounds, in the business plans of practically every business model. Methods are being refined and the search for the connection between brand and user is expected to become increasingly more precise: a related advertisement is no longer sufficient, now the advertisement must appear at the right time and in the right place. This is where categorization proves to be an exceedingly useful tool.

That is why, at MeaningCloud, we have improved our IAB categorization model in English, that is integrated in our Deep Categorization API:

  • Adding a third level of content taxonomy to the hierarchy of categories (IAB Taxonomy Level 3).
  • Improving the precision of pre-existing categories.
  • Including the unique identifiers defined by IAB itself for each of the categories.

Continue reading


Text Classification 2.0: Migration Guide

We’ve recently published a new version of our Text Classification API, which comes hand in hand with a new version of the Classification Models Customization console.

In both these new versions, the main focus is on user models. We know how important it is to easily define the exact criteria you need, so the new classification API supports a new type of resource, the one generated by the Classification Model Customization Console 2.0.

In this post, we will talk about how to migrate to these new versions if you are currently using the old ones. Text Classification 1.1 and Classification Models 1.0 will be retired on 15/Sep/2020. Continue reading


New Release: Text Classification 2.0

We’re happy to announce we have just published a new version of our Text Classification API, which comes hand in hand with a new version of the Classification Models Customization console.

In both these new versions, the main focus is on user-defined models. We know how important it is to easily define the exact criteria you need, so the new classification API supports a new type of resource, the one generated with the Classification Models Customization console 2.0.

With these new versions, we’ve aimed to:

  • Make criteria definition easier: more user-friendly operators to improve overall rule readability, and new operators to provide more flexibility.
  • Remove dependencies between categories in a model that made their maintenance and evolution cumbersome.
  • Give the user more control over where the relevance assigned to the categories comes from.
MeaningCloud release

Let’s see with a little more detail what’s new. Continue reading


Obtain deep customer insights with MeaningCloud

Companies need to analyze the feedback that customers provide to them through a variety of unstructured channels: surveys, interviews, contact center, social media. However, the text analytics solutions available are limited to a shallow analysis of the feedback. In this post we show you how to use deep analytics to get a complete picture of customer opinions, perceptions, emotions and intentions.

Companies need to become customer-focused in order to understand the needs and opinions of their customers and thus, define the proverbial “segment of 1”. This forces us to implement Voice of Customer (VoC) analysis initiatives that go far beyond the typical periodic satisfaction survey with numerical scores, to look for new sources of insights.

Continue reading


Recorded webinar: Deep text analytics to transform customer feedback into action

Last April 29th we delivered our webinar “Leverage deep text analytics to transform customer feedback into action”. Thank you all for your interest.

In it we explained how to use Meaning Cloud’s products in a synergic way to analyze your customer feedback through surveys, contact center interactions and social media, and level up your customer insights.

During the session we covered these items:

  • Leveraging unstructured customer feedback: benefits and challenges
  • Text analytics to the rescue… but with limitations
  • How to use deep text analytics to extract more actionable insights
    • Pre-made Insights
    • Adaptation
    • Development
  • understand the opinions, perceptions, emotions and intentions of your customers.

Interested? Here you have the presentation and the recording of the webinar.

(También presentamos este webinar en español. Tenéis la grabación aquí.)

Continue reading


Communication during the Coronavirus (I): Thematic analysis in Spanish digital news media

While it is obvious that the priority during this pandemic is to cure the sick, to prevent new cases from surfacing and to ensure there are economic and social measures in place to help the people and businesses most afflicted overcome the current situation; without a doubt, in the near future, the analysis of content related to the coronavirus that has been generated by the media and social network users will be the object of research for numerous disciplines such as sociology, philology, linguistics, audio-visual communication, and politics, to name a few.

At MeaningCloud we want to do our bit in this area, by applying our experience and our Text Analytics solutions to analyze the enormous volume of information in natural language, in Spanish and in other languages, in Spain and in other countries, given that, unfortunately, this is a global crisis.

This first article in the series centers on the thematic analysis of content that has been generated in Spanish by digital media platforms in Spain over the last month, how it has evolved during this period of time and the informative positioning of the main media platforms in Spain.

These other articles (only available, at the moment, in Spanish) analyse conversation topics on Twitter in Spain (both from the hashtags and general topics perspective and also applying a specific thematic categorization) and the linguistic analysis of presidential speeches related to this crisis.

Continue reading


Leverage deep text analytics to transform customer feedback into action (webinar)

Customer FeedbackOne of MeaningCloud’s goals is providing you with the best text analytics technology to help you better understand your customers and in recent times we have been launching products in this area: Voice of the Customer, Emotion Recognition, Intention Analysis.

But maybe you haven’t thought about how to use these products in a synergic way to analyze your customers’ feedback through surveys, contact center interactions and social media, and transform that feedback into action.

Continue reading