Latest qualitative methods in social science using big data
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Answer:
Explanation:
With the rapid increase of the sheer amount of social data produced and that is available, a particular recent trend for researchers from Social Sciences is to understand the potential of Big Data in complementing traditional research methods and their value in making decisions. Indeed, Big Data requires a revisit of data analysis techniques in fundamental ways at all stages from data acquisition and storage to data transformation and interpretation. In particular, the task of collecting and analyzing data — which is at the heart of the Big Data Analytics pipeline — underwent pressing (and somewhat daunting) challenges in the domain of Social Sciences. The types of available data fall into various categories: social data (e.g., Twitter feeds, Facebook likes), data about mobility and geospatial locations (e.g., sensor data collected through mobile phones or satellite images), data collected from government administrative sources and multi-lingual text datasets, only to name a few. In addition, data is often fragmented across many sources and often requires translation from one language (or specific format) to another and, in some extreme cases, a translation between different scientific disciplines is needed.