The predictive power of Social Media Analytics : To what extent can SM Analytics techniques be classified as reliable and valid predictive tools?

This critical literature review investigates three promising Forecasting / Social Media Analytics techniques: (1) trend analysis, (2) topic modeling and (3) sentiment analysis. To evaluate these methods, several assessment criteria are derived from Hammann & Erichson's (1994) criteria of market segmentation and prognosis. In total, there are five criteria which have to be taken into consideration, the criterion of observation, the criterion of measurement, the stability of the dataset, the purchasing relevance, and the criterion of homogeneity. To further question these forecasting methods in terms of methodological composition, several concepts of Babbie (2009) (validity & reliability) are used. Eventually, it is the goal of this critical evaluation to determine the predictive and analytic power of these forecasting methods resulting in a methodological taxonomy. In addition to this, the value of these techniques for Marketing strategy is questioned. In essence, it can be concluded that a large amount of managerial practitioners and scholars prognosticated Social Media and Big Data to facilitate Marketing activities such as market segmentation or the forecasting of customer behavior. However, it has to be emphasized that forecasting within social media environments is a sensitive undertaking bearing a large amount of potential research biases, may it be viewed from the quality of data or the sophistication of the forecasting method. This outcome calls for further research in the realm of Social Media Forecasting due to the fact that best forecasting practices have not been established yet.