We mined 6,000+ Season 8 Game of Thrones predictions on Reddit. Then we used our AI to analyze them. Here’s what we found.
The Blog.
Machine Learning Micromodels: More Data is Not Always Better
on
6 m
Machine learning micromodels reduce the challenges of sourcing and annotating data while delivering better precision and accuracy than macromodels.
Fight Organizational Bias with Unstructured Data
on
2 m
Efforts to fight organizational bias often fall short. Lexalytics CEO Jeff Catlin explains how to use unstructured data to fight your own company’s biases.
Measuring Media’s Impact on Financial Markets with Sentiment Analysis
on
1 m
Tim Mohler summarizes a recent paper in which researchers show how to measure the impact of media in global financial markets using sentiment analysis.
Let’s Talk AI Cooperation (Don’t Call it an “Arms Race”)
on
6 m
Advances in artificial intelligence are usually framed as an arms race. Instead, let’s look at AI research through the sunnier lens of cooperation.
Customer Feedback Analytics in Hospitality: Full Guide
on
15 m
We analyzed 50,000 TripAdvisor reviews of Best Western to demonstrate the value of customer feedback analytics in hospitality and other industries.
Voice of Employee Analytics: Step-by-Step Guide
on
16 m
HR teams use Voice of Employee analytics to gather, analyze and interpret employee feedback data to reduce turnover, improve productivity and more. In this article, Andrea Kulkarni demonstrates how you can do this without any coding or data science experience.
A Warm Welcome? Access to Advisory Services for Men and Women
on
1 m
Swedish researchers use Semantria for Excel from Lexalytics as well as the Swedish-Language Pack to identify evidence of sexism in a data set of emails.
The Ultimate NLP Tuning FAQ: Sentiment, Topics and More
on
11 m
Lexalytics Support Engineer Sarah Williams answers our users’ most frequently-asked questions about how to tune Lexalytics’ natural language processing.
Automatic Text Document Summarization Using Semantic-based Analysis
on
1 m
In this research article, Chandra Shekhar Yadav explains why Lexalytics’ algorithm outperforms previous text document summarization methodologies.
Deepfakes Explained: What, Why and How to Spot Them
on
7 m
As the 2020 elections loom near, AI-generated deepfakes are hitting the news cycle. But what are deepfakes? Why are they dangerous? And what can you do?
Variables of Twitter Activity That Influence Audience Spreading Behavior
on
1 m
What factors determine whether or not a brand’s Twitter content is shared among its audience? Luis Matosas López uses the Lexalytics Intelligence Platform to investigate these questions.