ABSTRACT
In the era of information explosion and the ease of Internet access, a tremendous amount of data is produced every second. Social media is a trendy platform for information distribution and discussions on various topics and events among different applications. Besides, people reflect their opinions through social media openly. Therefore, extracting insights from social media help decisionmakers craft better strategies. It can help them understand society’s views before quickly forming any firm action, which can be a game-changer. However, a large number of information sources co-exist, which creates substantial overlapping content, making insights extraction challenging and time-consuming. As a result, there is a significant necessity for an automatic summarization technique to extract a noise-free representative of the input sources. This chapter discusses the social data summarization problem from different perspectives.
