In today's era, social media has become a valuable source of information, where people express their opinions. Analysis of such opinion-related data can provide productive insights. When these opinions are relevant to a company, accurate analysis can provide them with information like product quality, influencers affecting other customer decisions, early feedback on newly launched products, company news, trends and also knowledge about their competitors. Hence, harnessing and extracting insights from these sentiments is necessary for these companies to implement effective marketing strategies and better customer service. Carrying the same notion forward, we decided to extract sentiments from Twitter relevant to two e-commerce giants in India, Flipkart and Snapdeal. In this paper, various lexicon based approaches are applied and their accuracy is investigated.
The advances in the digital world has rendered the collection of colossal amounts of data called Big Data. This voluminous data if analyzed in an expedient way can help us gain valuable insights. On the other hand, securing Big Data has become an important aspect as it can lead to disastrous results if intercepted by intruders. Through this paper, we describe the management of authentication and access control by providing an overview of the existing protocols. Further, we propose a modified protocol which amalgamates the authentication and authorization processes there by speeding up the entire procedure.
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