How to tell when negative sentiment becomes a threat to your business
Determining online sentiment doesn't just allow you to understand better how your brand is performing and how people feel about your business though. It can also be used to manage crises and spot potential threats to assets or staff.
Without sentiment analysis, data can be misleading. Sentiment gives data extra context which allows it to be better understood enabling a more effective and accurate response to the potential threat.
There are some 500 million tweets and over 4 million new blogs posted every single day. Each of these sparks another conversation which could house potential threats against an organisation. And we haven’t yet mentioned Facebook, Instagram, Reddit, Flickr, Medium or any of the other dozens of social sites and forums where people post online. And if you thought that was a lot of noise you have to remember the dark web too, where many cybercriminals go to engage in nefarious activities with the protection of a Tor browsers anonymity.
The point here is that the internet is full of noise. Monitoring all of that and then cutting through the noise to detect relevant potential threats requires the right tools.
What is Sentiment Analysis?
Determining online sentiment doesn't just allow you to understand better how your brand is performing and how people feel about your business. It can also be used to manage crises and spot potential threats to assets or staff.
Without sentiment analysis, data can be misleading. Sentiment gives data extra context which allows it to be better understood enabling a more effective and accurate response to the potential rtisks.
It also allows you to differentiate between when a negative comment is simply that, a negative comment, or when it needs more serious attention because, for example, it’s evolving into a physical threat.
Where and How do we Measure Sentiment?
Any text that gets highlighted by Signal OSINT software can be run through our sentiment analysis tool, Spotlight. This allows users to reduce the amount of noise and focus on the threats.
Sentiment can be expressed anywhere online, this might be through social media, in the comments of a blog or even in a dark web forum. Signal allows you to gather data from a huge array of open intelligence sources including (but not limited to) social media and dark web forums.
How can Sentiment Analysis Be Used for your Business?
Emerging Threats
Sentiment analysis can be an incredibly useful tool for those that wish to identify potential risks which might evolve into tangible reputational or physical threats against, employees, executives, brand or assets.
Managing Reputation
Your brand’s health and reputation are important. Having a tool that allows you to analyse the overall sentiment towards your brand and associated keywords gives organisations a bigger and better overall picture of their brand which can be a game-changer for launches of major events or analysing the success of a large marketing campaign.
Evolving Crises
When it comes to dealing with current and evolving crises having up to date and detailed situational awareness, gained through an OSINT tool such as Signal can make a huge difference. However, as we have mentioned before, there is a huge amount of noise out there. So, how do you determine which comments, which posts are relevant and need monitoring?
The answer is to use Signal to create specific filters and then run identified posts through our sentiment analysis tool “Spotlight”. This allows users to both quickly identify emerging threats and to then stay on top of these risks as they are evolving in real time.
Moving Your Marketing Forward
Social sentiment is a powerful tool for understanding the relationship between your brand, your customers, and your competitors. If you measure it regularly and act on what you learn, your team can create targeted marketing strategies to keep up with the ever-changing demands and opinions of your customers.
How do you determine when Negative Sentiment Becomes a Threat?
One of the key methods used by our software and our analysis team to tell whether or not a comment is a threat that needs more attention is the repetition of negative sentiment online by an individual or group.
For example:
Does a particular author of a comment or post have a long history of bad-mouthing an organisation or expressing negative sentiment?
Have they repeated the same negativity on multiple sources?
Even if they aren’t directly threatening any physical or tangible action against the organisation, if there’s enough online commentary from a single individual or group then this could escalate and it may be smart to further monitor.
You can then set up a search using our filters to target this individual or group so that you don’t miss if this negative sentiment becomes a physical or reputational threat.
Secondly, using Spotlight, users can identify posts expressing dangerous emotions such as anger, or disappointment. Both if repeated enough should be addressed. Posts expressing anger are likely to indicate a physical threat and should be monitored for that, whilst the posts expressing disappointment may hold reputational risks.
Summary
Sentiment analysis tools like Signal’s Spotlight can help security teams form a broader and more detailed overview of the situation to better understand the potential and emerging threats. It allows them to target their online searches and cut through the noise to identify key threats. All of this essentially means a more efficient and more effective security team.
You also might like:
Critical Security Intelligence for the Financial Services Sector
The Power of Emotional Analysis - introducing Signal Spotlight
In 2018 we launched Signal Spotlight! This feature allows users to analyse the emotion behind potential threats to determine associated risk. Signal users get a real-time overview of the emotional state of Signal search results to better understand the emotional drive behind identified threat intelligence.
Signal Spotlight provides a real-time overview of the emotional state of Signal search results. Using Signal Spotlight, Signal users can better understand the prevalence and drivers of emotions and what is happening in real-time.
Spotlight taps into the results from Signal search criteria across many data sources to better understand the prevalence and drivers of emotions. For example, during an incident or event, an important attribute is how people are feeling about what has happened and how the emotional state may be changing real-time as that incident/event unfolds.
The Spotlight underlying technology uses a large vocabulary of emotion terms that were compiled from multiple sources, including the ANEW and LIWC corpora, and a list of moods from LiveJournal. In addition, a crowdsourcing task was run to organise these terms against Parrott's hierarchy of emotions. The emotions are colour-coded using a dataset of affective norms provided by the Center for Reading Research at Ghent University.
Spotlight leverages technology and research undertaken by the Language and Social Computing team in the Digital Economy Programme of CSIRO's Digital Productivity Flagship and originally developed as a joint project between computer scientists at CSIRO and mental health researchers at The Black Dog Institute.
Reference
Milne, D., Paris, C., Christensen, H., Batterham, P. and O'Dea, B. (2015) We Feel: Taking the emotional pulse of the world. In the Proceedings of the 19th Triennial Congress of the International Ergonomics Association (IEA 2015), Melbourne, Victoria, Australia, August 2015.