


Volume 21 No 5 (2023)
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Perspectives and Challenges of Artificial Intelligence Techniques in Commercial Social Networks
Srinath Venkatesan
Abstract
Artificial intelligence (eat) methods and techniques have witnessed tremendous advances in the last ten years. They
have already made part of the usual landscape from where new or old problems are tackled in different areas of
human knowledge. Three particular aspects are behind this leap forward: a generalized availability and variety of
data, a deeper understanding of the mathematics governing the underlying algorithms, and hardware capabilities
allowing wide and deep experimental pipelines over data. The main challenge in each problem and application
context now lies in how these technologies can be used, their reach and limitations so that they can be aligned with
the aims of each specific problem. Social and communication sciences are no exception but show particularities that
define which eat technologies and methods are most appropriate (i.e. natural language processing). This work
introduces the methodology under which AI models are built for potentially useful eat services in the field and,
finally, some examples of applications illustrating practical and technical considerations.
Keywords
Artificial intelligence, machine learning, social sciences, data science
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