By Emily Jacobs
New social media insights into the current Australian Election have been derived using the solution SAP Social Media Analytics by Netbase.
The cloud-based solution quantifies online sentiment with a natural language processing engine and correlates changes in public opinion with campaigns, promotions, news and other events.
The solution was used to analyse the social media mentions of Tony Abbott and Kevin Rudd and key words associated with their respective campaigns.The analysis included multiple channels, including Twitter, Facebook, comments on news sites and online forums.
It revealed that while Tony Abbott generated more comments online overall, Kevin Rudd triggered more negative and more positive comments, as well as a slightly lower net sentiment. The results suggest that the online Australian public are more passionate about their views on Abbott.
The passion intensity score, which measures the amount of strong positive or negative emotions towards a brand, was much higher for the Liberal candidate.
In the time period, there were 38,364 posts about Abbott, with 6722 positive and 8020 negative mentions. His passion intensity score (spanning from 0 to 100) was 30. In contrast, there were 35,253 posts about the current Prime Minister, with 7380 positive and 9200 negative mentions. His passion intensity score was 10.
However, perceptions of the candidates changed based on key election topics. Abbott outscored Rudd in net sentiment on ‘trust’ and ‘leadership’, but Rudd rated higher in relation to ‘same-sex marriage’ and ‘asylum seekers’.
Thomas Tudehope, a political social media commentator says negativity is normal.
“It’s not unusual to see this level of negativity surrounding politicians and online commentary,” he said. “Rudd is suffering in the trust stakes, while Aboott’s thorn in his side is around asylum seekers.”
The unique passion intensity score is calculated using a formula that takes into account the number of strong and weak emotions (both good and bad) within posts. Examples of the key words to indicate emotion include ‘adore’, ‘love’, ‘best’, ‘brilliant’ for strong positive and ‘abysmal’, ‘disastrous’, ‘offensive’ and ‘hate’ for strong negative. Weak positive words include ‘adequate’, ‘decent’, ‘fine’, ‘nice’ whilst words like ‘bad’, ‘confuse’, ‘dislike’ and ‘poor’ were considered weak negative words.
Businesses can implement SAP Social Media Analytics by Netbase to calculate similar insights from prospects and customers. It enables organisations to monitor and respond to market trends, quantify market perceptions and track success.
David Foulcher, head of cloud for customer and money at SAP Australia and New Zealand says social media analysis is an essential part of customer relations.
“In both the public and private sectors, social media sentiment analysis is an increasingly important component of understanding your stakeholders and customers,” he said. “With more empowered consumers and more of the buying process happening before the first interaction with a sales representative, businesses need to uncover insights, trends, emotions and behaviour as they look to convert prospects not just to customers but to promoters.”
