Studying social media sentiment using human validated analysis

Abstract

The measurement of online sentiment is a developing field in social science and big data research. The methodology from this study provides an analysis of online sentiment using a unique combination of NLP and human validation techniques in order to create net sentiment scores and categorise topics of online conversation. The study focused on measuring the online sentiment of South Africa's major banks (covering almost the entire retail banking industry) over a 12-month period. Through this methodology, firms are able to track shifts in online sentiment (including extreme firestorms) as well as to monitor relevant conversation topics. To date, no published methodology combines the use of big data NLP and human validation in such a structured way. • Microsampling for manual validation of sentiment analysis (both qualitative and quantitative approaches in order to obtain the most accurate results) • Sentiment measurement • Sentiment map

Keywords

• Social media
• Negative word-of-mouth (nWOM)
• Online firestorms
• Consumer sentiment