# Automatic Short Text Summarization Techniques in Social Media Platforms
## 1 Introduction  
### Background  
In recent years, the landscape of communication has undergone a profound transformation with the ascendancy of social media platforms such as Twitter, Sina Weibo, and Facebook. These digital forums have swiftly emerged as primary conduits for real-time dissemination of news and updates, creating an unprecedented synergy between information and immediacy. Nevertheless, this surge in activity has engendered a proliferation of data on a staggering scale, posing a formidable challenge for users striving to unearth the precise morsels of information they seek. The sheer volume and the accelerated pace of data generation within these platforms have ushered in an era of information abundance that, paradoxically, obscures the very insights users aim to glean. At the nexus of this challenge lies the practice of manual text summarization--an art that entails extracting the vital essence from a document. This process, though imbued with the power to distill significance, exacts a toll on time and resources, especially when faced with substantial textual corpora. The indispensability of manual summarization reverberates across fields as diverse as journalism, research, and academia, where distilled and meticulous summaries stand as pillars of knowledge dissemination [1]. The tide of innovation, however, has bestowed upon us the mantle of automation. Text summarization, with its intricate web of algorithms and linguistic nuances, has burgeoned into a field of study that embodies the duality of precision and automation [2]. This evolution materializes in two principal strands: extractive techniques, adept at selecting and weaving key sentences into succinctnarratives, and abstractive techniques, proficient at birthing new sentences that encapsulate the quintessence of the original text. These methodologies, once honed, find homes in an array of applications: news condensation, social media abstraction, and scientific exposition [3]. Yet, amid these strides, a noteworthy chasm persists--a divide that underscores the prowess of human summarization over its automated counterparts. This divide emerges from the intricate choreography of comprehension, where the holistic significance of text passages dances to the tune of myriad factors. The subtleties of context, tone, and intent conspire to elevate human summarization above its algorithmic brethren. Thus emerges the clarion call--a resounding summons--to ascend the peaks of automation and engender algorithms of enhanced potency. This clarion call is resolute in its quest to bridge the gap and align the efficacy of automated short text summarization (ASTS) techniques with their human counterparts. Within the realm of social media and microblogs, ASTS unfurls as a grand enterprise akin to Multi-Document Summarization (MDS), a domain meticulously explored in the annals of information retrieval [4]. This paradigm equips users with the power to deftly distill cardinal insights from a multitude of documents, weaving them into concise narratives that encapsulate specific topics or events. Yet, this realm is riddled with the challenge of redundancy--an abundance of information that often conceals rather than reveals. The task of sieving through this labyrinth of extraneous data calls for strategic data reduction and adept summarization techniques that, when forged, yield succinct gems of insight. In the tapestry of social media and microblogging, the threads of summarization weave an invaluable tapestry. This tapestry emerges as concise summaries, capturing the essence of real-time dialogues surrounding specific topics or events. The significance of these summaries extends to individuals, enterprises, agencies, and organizations seeking to fathom the prevailing public sentiment--a virtual looking glass into the collective voice [5].