Efficient Pre-processing and Feature Selection for Clustering of Cancer Tweets

Lavanya, P. G.; Kouser, K.; Suresha, M

doi:10.1007/978-981-13-6095-4_2

Cited by 4 publications

(1 citation statement)

References 14 publications

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“…The research conducted by Lavanya et al was centered on analyzing Twitter data related to cancer [49]. They collected data continuously over the course of one year and recorded observations comparing two sets of data.…”

Section: Asts Techniques For Social Media Platformsmentioning

confidence: 99%

Automatic Short Text Summarization Techniques in Social Media Platforms

Ghanem,

Padma,

Alkhatib

2023

Future Internet

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The rapid expansion of social media platforms has resulted in an unprecedented surge of short text content being generated on a daily basis. Extracting valuable insights and patterns from this vast volume of textual data necessitates specialized techniques that can effectively condense information while preserving its core essence. In response to this challenge, automatic short text summarization (ASTS) techniques have emerged as a compelling solution, gaining significant importance in their development. This paper delves into the domain of summarizing short text on social media, exploring various types of short text and the associated challenges they present. It also investigates the approaches employed to generate concise and meaningful summaries. By providing a survey of the latest methods and potential avenues for future research, this paper contributes to the advancement of ASTS in the ever-evolving landscape of social media communication.

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Section: Asts Techniques For Social Media Platformsmentioning

confidence: 99%