Doug Jones is heading into tomorrow's Senate Election in Alabama with a small but growing lead over Roy Moore. After being tied at the end of last week, Jones has started to add support over the past couple of days to move ahead 54-46.
Since Eyesover uses online data for its polling, determining the location of a specific account is not always possible if the account owner chooses not to publish their location. However, Eyesover can segment the individuals discussing the Alabama election online into groups of people who are from Alabama and those who have no confirmed location (they may be from Alabama or any other location).
The variance in support levels between these two groups is interesting as the Alabama group shows the 54-46 lead for Jones while the data from the Unconfirmed Location (UL) group shows a closer race at 51-49 for Jones.
When we dive down into the issues these groups are discussing in relation to the election, the Alabama group's top issue is Healthcare while the UL group's top issue is Human Rights/Women's Issues.
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