Over a Decade of Social Opinion Mining
- URL: http://arxiv.org/abs/2012.03091v1
- Date: Sat, 5 Dec 2020 17:59:59 GMT
- Title: Over a Decade of Social Opinion Mining
- Authors: Keith Cortis and Brian Davis
- Abstract summary: This systematic review focuses on the evolving research area of Social Opinion Mining.
Natural language can be understood in terms of the different opinion dimensions, as expressed by humans.
Future research directions are presented, whereas further research and development has the potential of leaving a wider academic and societal impact.
- Score: 1.0152838128195467
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Social media popularity and importance is on the increase, due to people
using it for various types of social interaction across multiple channels. This
social interaction by online users includes submission of feedback, opinions
and recommendations about various individuals, entities, topics, and events.
This systematic review focuses on the evolving research area of Social Opinion
Mining, tasked with the identification of multiple opinion dimensions, such as
subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from
user-generated content represented across multiple social media platforms and
in various media formats, like text, image, video and audio. Therefore, through
Social Opinion Mining, natural language can be understood in terms of the
different opinion dimensions, as expressed by humans. This contributes towards
the evolution of Artificial Intelligence, which in turn helps the advancement
of several real-world use cases, such as customer service and decision making.
A thorough systematic review was carried out on Social Opinion Mining research
which totals 485 studies and spans a period of twelve years between 2007 and
2018. The in-depth analysis focuses on the social media platforms, techniques,
social datasets, language, modality, tools and technologies, natural language
processing tasks and other aspects derived from the published studies. Such
multi-source information fusion plays a fundamental role in mining of people's
social opinions from social media platforms. These can be utilised in many
application areas, ranging from marketing, advertising and sales for
product/service management, and in multiple domains and industries, such as
politics, technology, finance, healthcare, sports and government. Future
research directions are presented, whereas further research and development has
the potential of leaving a wider academic and societal impact.
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