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This study examined the differences in social media sentiment based on author gender, age and country. After creating ten category-generic datasets, millions of social media verbatims from thousands of websites were collected, cleaned of spam, and scored into five-point sentiment scales. The results showed that women exhibit more positive sentiment, older people exhibit more positive sentiment, and Australians exhibit more positive sentiment, while Americans share more negative sentiment. The differences were small but clear, suggesting that research methodologists should apply correction factors to ensure that their results more accurately reflect differences of opinion as opposed to differences of word choice. Business users of social media data can be reassured that correction factors are not required to improve the accuracy of their research. [ABSTRACT FROM AUTHOR]

The article focuses on the promises and pitfalls of social media research (SMR) as a study of gathering data by passive online listening techniques. It says that SMR promises 10,000 small sample sizes which reduce people's reliance on survey volunteers, while listen vs. ask opposes an asking process in which researchers work hard from consumers' responses. It mentions the perils face by SMR such as lack of validation research and fear-based resistance. It adds that the cooperation of information technology (IT) professionals and business analysts progressed wherein they analyze to evaluate social media data and track brand performance.