Sentiment Analysis is a vital tool for public relations (PR), media relations and communication professionals – not just to ensure they are making the most out of media monitoring, but also in strategic planning.
It allows a measure of the mood around a brand, sector or industry that goes way beyond a basic count of mentions.
Sentiment analysis enables the assessment of the positivity of news, coverage and reaction. It provides a gauge of feelings held and responses provoked to help demonstrate the success of activity, to shape future plans and to initiate action.
Sentiment Analysis is the process of understanding the meaning behind the words spoken online and in the media and powers effective media monitoring.
It allows PR professionals to grade whether articles, social media posts or broadcasts are substantially positive, negative or neutral.
You can attempt sentiment analysis manually, but doing so effectively and comprehensively in a world of never ending online, broadcast, print and social media output is time consuming to a point that it can mean that urgent responsive action is delayed or becomes too late to implement.
Artificial intelligence (AI) tools have automated sentiment analysis to allow it to be achieved across many forms of media and online output for many topics extremely quickly and effectively.
Via AI software and products, sentiment analysis tools can be used to sort through vast quantities of published and broadcast reports and comments to sort it by topic into ‘positive,’ ‘negative’ and ‘neutral’.
The table below offers a simplified idea of the insight given:
|‘Sentiment analysis is amazing!’||Positive|
|‘I hate sentiment analysis’||Negative|
|‘A definition of sentiment analysis’||Neutral|
Sentiment analysis is just one phrase within the ever growing glossary of PR and media intelligence terms.
For PR, media relations and communications teams, sentiment analysis is particularly used to gauge whether what is said about your brand, competitors and industry is positive, negative or neutral.
Too much neutral chatter may imply missed opportunities to promote the activity of your business or organisation.
Positive mentions indicate that current activities are proving successful, which is good for demonstrating results, but also contributes to future planning.
Knowing how popular an initiative has been can help in planning how to manage comms around any changes, for example if a bank has to end a particular offer for its customers. Monitoring the sentiment around the offer can tell you how popular it’s been.
Negative mentions can show a need for a change of communications or business direction – or merely a need to respond in order to manage the situation and influence the conversation.
Sentiment analysis helps to demonstrate genuine value in PR campaigns, to shape future campaigns, manage reputation, gain insight into competitors and keep your finger on the pulse during crisis management situations.
Sentiment analysis is a measurement of media coverage and PR value that dates vanity tools and measures such as advertising value equivalency (AVE) and other tactics. It is a measure that drives continually improving performance and shows the value of PR to the C-suite by adding meaning within reports.
Sentiment analysis is an area in which AI is revolutionising PR.
Daniel Batchelor, Global Head of Corporate Communications at travel technology firm Amadeus, said: “To inform our overall business strategy, we needed a solution to benchmark, sense check and understand how stakeholders and customers are reacting globally to the brand and its products.
“We can look at the quantity and quality of our coverage across various topics and visibly compare that with our competitors.”
To be truly effective, sentiment analysis software needs to be able to have an understanding of slang, sarcasm and nuance.
Words such as ‘sick’ and ‘bad’ change meanings with time and can prove a challenge for less advanced sentiment analysis tools. Similarly, certain words used in different ways can convey opposite meanings – such as ‘the call wait times are killing me’ as opposed to ‘this product is really killing it’.
Emojis are now frequently used by people to express emotion and could prove a challenge for some sentiment analysis tools.
Sentiment analysis tools also need to be set up and trained to cope across multiple languages where required.
Signal AI’s analysis of advertising campaigns by three different challenger banks on the London Underground provided interesting insight into their comparable success.
The team behind the campaign for one bank – Revolut – achieved the second highest volume of coverage, but only 16.6% classified as positive.
Monzo’s campaign, meanwhile, generated the least amount of coverage, but 30.2% was positive.
Starling, meanwhile, got the most coverage and the most positive coverage. A total of 67.4% of analysed mentions in regard to the campaign were positive.
This is a great example of how a look at sentiment analysis may influence how the success of a campaign is perceived.
Sentiment analysis is a powerful measure, but is only one measure – and other factors are imperative in terms of a rounded assessment of the outcomes of campaigns. If mass coverage is achieved and the majority of it is neutral, or even negative, it may still raise the profile of a product or service to the point of achieving increased sales, for example, which may have been the primary objective.
Sentiment analysis should be an integral part of any media monitoring software.
Top tips for sentiment analysis usage include:
The best sentiment analysis tools need to be able to be able to be trained to recognise a high level of nuance, to offer flexibility for adjustment to meet your specific requirements and be able to react to and deal with the complex nature of language and communications.
Sarcasm and words that have dual meanings can throw less sophisticated sentiment analysis tools off. That is especially true of those words that can mean the opposite of their original intended definition, such as ‘sick’ for ‘great’ and ‘extra’ as a negative for being a bit fake or over-the-top.
Signal AI takes great care to get this right.
Effective sentiment analysis tools and reporting are part of the Signal AI platform.
Benjamin Thiele-Long is Director at Cognito – a PR, marketing and communications agency – and he told us how our software enables his business to create meaningful reports to demonstrate the value of its work to clients.
He said: “Hits for the sake of it is never going to impress a board or a C suite but actually understanding the value of why a particular media programme was useful, how it leads to sales generation, how it leads to awareness, how it leads to brand value, is all important.
“Being able to do that by understanding ‘share of voice’, how it works with competitors, what it meant in the landscape as a whole, is really useful for that.
“It also is useful to understand where things didn’t work well because you can put that into context and realise how you might do something differently and that informed process is really what KPIs for PR programmes and media should really be about.
“To provide meaningful insight but also staying as alert in real time as much as possible to what’s happening. That push and pull of understanding the data and information flow that’s key to the job and that’s something that I rely on every single day.”
Signal AI technology offers real-time insight and alerts to global print, online and broadcast media to support PR and communications professionals in crisis and reputation management, media planning and reporting. Sentiment analysis is part of that offer.
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