The dataset has 25000 positive and negative reviews in the training set and 25000 positive and negative reviews in the test set. The image below shows the number of unique reviews and unique sentiment values in the dataset. The movie reviews are classified as having either a positive sentiment or a negative sentiment. The image below takes a peek at four reviews and their target sentiments. As can be seen from the keywords of the first three reviews – hooked, wonderful, unassuming, wonderful – lend the review a positive connotation.

This article is based on a presentation given by Emerj CEO Daniel Faggella in Geneva, at the 2019 New Shape Forum: Weapons Governance for the Geneva Disarmament Platform. To learn more about Emerj's AI presentations and speaking, visit our presentations page. There are many more AI applications than there are governments and militaries experimenting with AI. But the AI products that are becoming more commonplace in the business world do have their use in national security and defense efforts. It will take years to update physical weapons systems, such as tanks, planes, and missiles, with machine learning technology, but there are ways to weaponize artificial intelligence without mounting it on any weapons.

Before delving into the nitty gritty of exactly how sentiment analysis works, let's break the concept down into something a little more tangible, shall we. Have you ever wondered what the South African public thought about, let's say, Iceland's football team defeating England in the Euro 2016? Well, that right there my friends, is why sentiment analysis software exists – to make vast quantities of data easily understandable at a glance. Think of it like a snapshot of the emotional response to a given topic. You might be asking yourself, but what about online surveys and polls, isn't that their purpose?

Organizations have generated unprecedented amounts of employee feedback through weekly or monthly pulse surveys, annual engagement surveys, and internal social networks and collaboration platforms. But many still struggle with how to efficiently comb through that mountain of information to identify actionable insights leaders can use to improve employee engagement and retention. Some companies are now turning to artificial intelligence (AI) tools to conduct sentiment analysis on employee feedback, gauge how employees feel and address their concerns. While text analysis of survey responses isn't new, the emergence of smarter algorithms enables faster and more precise search and categorization of unstructured data, such as open-ended comments, said Alan Lepofsky, vice president and principal analyst with Constellation Research, a technology research firm in Silicon Valley. Lepofsky, author of the recent report Why Artificial Intelligence Will Power the Future of Work, said vendors have made advances in sentiment analysis technology.