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The emergence of social network site has attracted many users across the world to share their feeling, news, achievements and personal thoughts over several platforms. The recent crisis due to worldwide lockdown amid COVID 19 has shown how these online social platforms have grown stronger and turned up as the major source of connection among people when there is social distancing everywhere. Therefore, we have surveyed Twitter users and their mannerism with respect to languages, frequency of tweets, the region of belonging, etc. The above observations have been considered especially with respect to Saudi Arabia. An insightful analysis of the tweets and twitter handles of the kingdom has been presented. The results show some interesting facts that are envisaged to lay a platform for further research in the field of social, political and data sciences related to the Middle East.

The popularity of the online media-driven social network relation is proven in today's digital era. The many challenges that these emergence has created include a huge growing network of social relations, and the large amount of data which is continuously been generated via the different platform of social networking sites, viz. Facebook, Twitter, LinkedIn, Instagram, etc. These data are Personally Identifiable Information (PII) of the users which are also publicly available for some platform, and others allow with some restricted permission to download it for research purposes. The users' accessible data help in providing with better recommendation services to users, however, the PII can be used to embezzle the users and cause severe detriment to them. Hence, it is crucial to maintain the users' privacy while providing their PII accessible for various services. Therefore, it is a burning issue to come up with an approach that can help the users in getting better recommendation services without their privacy being harmed. In this paper, a framework is suggested for the same. Further, how data through Twitter API can be crawled and used has been extensively discussed. In addition to this, various security and legal perspectives regarding PII while crawling the data is highlighted. We believe the presented approach in this paper can serve as a benchmark for future research in the field of data privacy.

The need for a comprehensive study to explore various aspects of online social media has been instigated by many researchers. This paper gives an insight into the social platform, Twitter. In this present work, we have illustrated stepwise procedure for crawling the data and discuss the key issues related to extracting associated features that can be useful in Twitter-related research while crawling these data from Application Programming Interfaces (APIs). Further, the data that comprises of over 86 million tweets have been analysed from various perspective including the most used languages, most frequent words, most frequent users, countries with most and least tweets and re-tweets, etc. The analysis reveals that the users' data associated with Twitter has a high affinity for researches in the various domain that includes politics, social science, economics, and linguistics, etc. In addition, the relation between Twitter users of a country and its human development index has been identified. It is observed that countries with very high human development indices have a relatively higher number of tweets compared to low human development indices countries. It is envisaged that the present study shall open many doors of researches in information processing and data science.