Through the analysis of online conversations, Eyesover provides real-time polls indicating the public's support (or lack thereof) for the topic of the conversation. Many of our customers use this polling ability in the political sector. Eyesover listens, analyzes, and tracks how much public support each political party or candidate is getting compared with their competition.
So how do we determine public support? To answer this question, we looked at what it means to be considered a supporter.
Consider how one might learn about a friend's favorite sports team? One way is to ask them - this is how traditional polls work. The poll would ask a question and provide options to choose from. A different way to find out what your friend's favorite sports team is, would be to just listen to them. Typically, if someone is vocal about their opinions then it generally doesn't take long to learn where that person stands on different topics. Even if someone isn't very vocal, we often learn a lot from normal, everyday conversations with each other. The key here is listening. Listen to what people are saying and learn from it. Even without asking a question, it is not difficult to tell if someone is opinionated about specific topics based on how much they keep bringing up the topic.
We took these concepts and applied them to how we find supporters within the social media landscape. Our customers simply choose which subjects, such as two competing politicians, they would like to find public support for and our system then listens to all online conversations taking place about those politicians. By listening to these conversations, Eyesover is able to determine if people on social media are (a) interested in a subject, based on how much they discuss it, and (b) how they feel about that subject.
Through our product development, we have learned how much discussion and what sentiment is required to confidently state an individual is a supporter or an idea, brand or individual. The analysis is performed for every “vote” in our poll in real-time. In fact, Eyesover's polling system calculates over 10 million voters every hour, and as the search for discussion grows through our AI technology, more voters are calculated every day.
Determining a supporter has far reaching benefits. Not only does this provide accurate predictions for such things as political elections, it also provides our customers with a deep understanding about the critical opinions influencing their audience.
The strong lead Doug Jones held in the Alabama Senate race last week is all but gone as Roy Moore's support has rebounded driving Jones' lead down to 4 points.
As a result of Jones' lead last week, it appears that Moore supporters have become more engaged as there has been an increase in the number of individuals talking negatively about Jones online, while discussions about Moore have become more positive.
While 90% of last week's discussions pertaining to the race were about Moore, we now see a 60-40 split between Moore and Jones. The issue for Jones is his sentiment scores have fallen from an overall positive to an overall negative in a relatively short period of time.
Today's Eyesover Support Index indicates that Alabama Republican Senate candidate Roy Moore has been unable to stop the erosion of his support over the past week and now trails Democratic candidate Doug Jones by 12 points.
Over the past week there has been 10x more online discussion pertaining to Moore than Jones, but the overwhelming majority of those discussions have been marked with very negative sentiment towards Moore, the cause of his deteriorating support.
Jones has been in the background while Moore has been the focus of the media over the past week, but he will clearly be attracting more attention from all sides now that the race is competitive. With his online mentions increasing over the past two days, we'll be watching to see how it will affect his sentiment and support scores.
Mention count, number of views, expected reach; these are just a few of the terms used by the social media marketers, but what does this information really tell us?
A major problem with online metrics is the potential for mention count to be manipulated by multiple mentions coming from both legitimate accounts and bots. Hundreds of comments, likes, or retweets from the same account will obviously inflate metrics, sometimes to the point where wrong decisions are made based on the flawed data.
Similarly, this inaccuracy can apply to the ‘number of views’ or expected reach. Often, neither metric will give you accurate information regarding the number of unique individuals who viewed your article or video if the numbers are inflated by individuals using different devices or web browsers.
The same holds true for inbound content. Knowing exactly how many individuals are talking about a particular subject can be far more valuable than just knowing how many mentions there are. Too many times organizations will be put on full alert and devote resources to an issue that is rapidly growing in mentions online, yet the reality is the mentions are coming from a handful of accounts.
One of the unique features of the Eyesover system is that we analyze our data on an individual by individual basis. This gives us the ability to report not only on the number of mentions, but also, the far more important metric of the number of individuals that are actually talking about the subject.
This method cuts through the spam and counts high volume accounts as exactly one individual, regardless of how many tweets they posted that day. By analyzing online content in this manner, we not only identify and discover real trends as they develop, we can use the individual opinions for key features such as our real-time polling and ad targeting while ensuring users are not distracted by noise.
Eyesover Technologies Releases New Issue Discovery Software
Fredericton, New Brunswick, Nov. 22, 2016 – Eyesover Technologies Inc. is pleased to announce the release of their new Issue Discovery module as the latest addition to their online media monitoring system.
Utilizing Eyesover’s proprietary artificial intelligence, the new Issue Discovery module provides customers with a predictive tool that identifies online discussions or mentions of new issues that are relevant to the end user.
“The limitation of most social media monitoring tools is selection bias – a system will only report on what you tell it to monitor. Eyesover’s new Issue Discovery module can extrapolate from existing data to see the potential development of issues a customer may not be aware of.” said Eyesover co-founder Dr. Ali Ghorbani, Canada Research Chair in Cybersecurity, Dean of the Faculty of Computer Science at the University of New Brunswick, and the Director of the Canadian Institute for Cybersecurity.
The Eyesover system now provides customers with online media monitoring and analysis, real-time lead generation, and the new issue discovery functionality to enhance the depth of information customers are obtaining from online media.
“We’re looking to take social media monitoring into the next stage where we’re not just listening, we’re predicting what is going to occur. The Issue Discovery module is a big step in that direction that will bring benefits to a wide range of private, public and non-profit entities.” said Eyesover co-founder and CEO Craig Leonard.
About Eyesover Technologies
Established in 2014, Eyesover provides an online media monitoring and issues discovery solution for customers including political parties, utilities, public and private sector corporations and governments.
The system is the product of research from the Intelligent and Adaptive Systems (IAS) Research Group within the Faculty of Computer Science at the University of New Brunswick, led by Dr. Ali Ghorbani.
For more information, visit www.eyesover.com
Contact: Craig Leonard, CEO
46 Dineen Drive