Introduction to Social Media Analysis

Social media is a phenomenon that has recently expanded throughout the world and quickly attracted billions of users. This form of electronic communication through social networking platforms allows users to generate its content and share it in various forms of information, personal words, pictures, audio, and videos. Therefore, social computing is formed as an emerging area of research and development that includes a wide range of topics such as web semantics, artificial intelligence, natural language processing, network analysis, and big data analytics.

Over the past few years, online social networking sites (Facebook, Twitter, YouTube, Flickr, MySpace, LinkedIn, Metacafe, Vimeo, etc.) have revolutionized the way we communicate with individuals, groups, and communities, and have altered everyday practices. One only needs to look at the recent statistics to prove this fact. 

                                                                                                                        (source: Our World In Data)

There are several means of interaction in social media platforms. One of the most important is via text posts. The natural language processing (NLP) of traditional media such as written news and articles has been a popular research topic over the past 25 years. NLP typically enables computers to derive meaning from natural language input using the knowledge from computer science, artificial intelligence, and linguistics.

NLP for social media text is a new research area, and it requires adapting the traditional NLP methods to these kinds of texts or developing new methods suitable for information extraction and other tasks in the context of social media.

A social network is made up of a set of actors (such as individuals or organizations) and a set of binary relations between these actors (such as relationships, connections, or interactions). From a social network perspective, the goal is to model the structure of a social group to identify how this structure influences other variables and how structures change over time. Semantic analysis in social media (SASM) is the semantic processing of the text messages as well as of the meta-data, in order to build intelligent applications based on social media data.

There are several tasks that can be performed for the natural language processing of data from social media. Some of these include named entity recognition, key phrase extraction, unigram analysis etc. These will be elaborated on in the several upcoming blog posts on this website. 

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