Facebook is the most popular social media platform all over the world and a huge data repository that can be analyzed to predict events as people express their thoughts on this platform. There are some events that often turn into potential crises and these crises might be avoided if we can predict it earlier. This work aims to predict events that are happening or going to happen by analyzing Bengali Facebook posts and help authorities to take proper security arrangements. In this work, the Naïve Bayes Classification model has been used to classify posts as an event. Tokenization, Stopwords removing have been used for data pre-processing. Event phrase matching and 2-Layer Filtering have been used for features collection. Sentiment scores have been measured using Valence Aware Dictionary and Sentiment Reasoner(VADER). Finally, this work predicts four types of events(protesting, celebrating, religious, and neutral) showing 87.5% accuracy. Keywords Event prediction • Naive Bayes • Sentiment analysis • Social media •

This study provides an overview of the seasonal variation on catch composition, the pattern of gear used and their effects on fish production and management system of north-western part of the Chalan beel. Results of the study revealed that annual beel cycle can be divided into four phases namely, resting, preparatory, growing and decay. Harvesting of fishes in chalan beel was done by using a variety of fishing gears. A total of 27 different types of fishing gears were recorded during investigation period from the study area of the beel. Recorded fishing gears were categorized into three major types which were net, trap and wounding gear. Marked seasonal variation was observed in the use of gears which mostly dependent on the flooding and water depths of the beel. A total of 62 fish species were recorded from this study area including 51 indigenous fish species and 11 exotic species. Fishes were recorded under following 12 fish orders-Cypriniformes, Siluriformes, Perciformes, Channiformes, Mastacembeliformes, Clupeiformes, Osteoglossiformes, Cyprinodontiformes, Anguiliformes, Synbranchiformes, Beloniformes and Tetraodontiformes. Some gears like Shuti jal, Current jal, Khora jal, Ber jal/Badai jal and some traps and specialized fishing methods were identified as very harmful to the sustainable production of the beel as well as to the wild brood stock of these natural water bodies. About 8 fish species were recorded as threatened species due to irresponsible fishing. Overall fish production level of the study area was not satisfactory which ranged from 350-400 kg/ha/yr.

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The scope and area of Big Data have gained significant momentum from the tandem of academics and business parlance over the last couple of decades. It assists organizations in gaining business insights, fostering a competitive edge, and transforming whole business processes (Dahiya et al., 2021; Shah, 2022; Talwar et al., 2021; Wamba & Mishra, 2017). According to McKinsey (2011), Big Data would be a unique source of improving the productivity, competitiveness, and innovation of the business organization. Similarly, McAfee et al. (2012) argued that Big Data can enhance the entire decision-making function of a firm. According to Brown et al. (2011), the reasoning behind this transformation of the entire decision-making function of a firm lies in the caliber of Big Data to change the footprint of competitiveness by fostering innovation, shifting business ecosystems, and revamping business processes. Therefore, it is significant to study Big Data due to its enormous capability of transforming entire business processes. Scholars have argued that competitive advantage in this era comprehensively depends on……..