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Actor Network Theory

Why It Is Suitable for Studying Computing?

The concept of contemporary computing came into light in the nineteenth centuries. The evolution of computing has marked the advancement of core computing with the invention of new and smarter technologies over the years. An assemblage of modern computing refers to the development of new and over the top technological inventions with advanced software and hardware mechanisms, improved CPU processing speed, development of networking and database security measures which provides with increased speed of performance and productivity (Shen and Qian, 2014). The fast paced life of today is made a lot easier and smoother with the innovation of modern computing technologies. Contemporary computing brought in the use of fast and automated electronic devices for computing tasks. The study of Science and Technology provides us with a clear idea of the effects and impacts of modern or contemporary computing technologies and the immense changes it has brought to our way of living.

Actor Network Theory was developed in the year 1960. According to the creator of ANT, Bruno Latour and Michel Callon, it is a theory that is based on the social and technological attributes discussed under the Studies of Science and Technology. It mainly deals with the man-machine interactions. The relationship between humans and electronic machines has greatly evolved and, in fact, grew deeper and stronger with the advancement of new technologies and modern computing. The actor-network theory states that there are both human actors and non-human actors involved in a given system. The story surrounding the whole system is analysed on the basis of ANT. ANT theory perceives the system from sociological as well as a technological viewpoint. Today’s generation of people has both a social and online existence (Singh and Reddy, 2014). The actor-network theory considers both these perspectives. In sociological science, the human actors and non-human-actors participates in the whole system of activity that is considered as the network. How these actors shape the network is analysed in this theory. The actor-network theory occupies a significant amount of space in the Science and Technology Studies. The ANT writers refer to these human and non-human entities as “actants. The term “token” is used to mention to the objects passed between the actants. ANT covers a large aspect of questions and answers most of which are related to the use of technology, its relationship with the society, how and why we use these technologies and its effects on our lives.

Why It Is Suitable for Studying Computing

The study of A.N.T. is beneficial for several aspects of science and computing. It helps us figure out the sociological and technological relationships among the entities or “actants” (both human and non-human). It is possible to analyse multiple aspects of a certain technology on the basis of ANT and determine the negative as well as positive impacts on it on the society and culture. The study of ANT can be hugely associated with modern computing as it is considered to be a part of sociological studies but also a part of Science and Technology. To fully understand the theory of ANT a basic knowledge in networking is necessary which is obviously related to computing or technical aspect of the study (Newcombe et al., 2015). The reason behind this is ANT fundamentally deals with the characteristics of networking and actors mostly by evaluating case studies, surveys or statistical analysis. Typically, the social study of technology requires a knowledge base for computing so as to distinguish the level of modernity of technologies and technical factors that affects social studies.

The numerous success stories of Amazon Web Services (AWS) guarantee the immense advantages and usefulness of implementing cloud computing in e-commerce industries. The Amazon Web Services or AWS provides cloud computing services in a cloud-based platform. AWS first started to offer its cloud services in the year 2006. Their main intention was to facilitate websites and client-side applications with the online cloud-based services. Today, AWS has experienced tremendous success and growth and has evolved and emerged with a wide variety and number of diverse services such as CloudDrive, Elastic Compute Cloud (EC2), CloudSearch, Distributed Cloud, Dynamo Database (DynamoDB), Simple Storage Service (S3) and lots more (Bernstein, 2015). The AWS Cloud has a strong partnership with most of the world’s largest and growing community of companies. The technology and consulting partners of AWS offers a wide range of products and services on Amazon’s cloud platform. AWS has multiple data centres located in the cities of U.S., Singapore, Brazil, Japan, Europe and Australia with its customer base spread across 190 countries and numerous different industries.

Amazon.com is the world’s largest retailing website or online supermarket. In the year 2011, Amazon.com switched to using ‘Amazon S3’ for most of its storage space requirements of Oracle databases (Duan and Xiong, 2015). After migrating to S3, Amazon has witnessed lots of benefits along its way with regards to data storage. Easy implementation, availability and durability of data, reduction of expenditures, backups, etc. are few of them.

Story 1: e-Commerce on the Cloud

Actants: on the basis of Actor Network Theory, the overall impact of migrating to cloud-based technologies in e-commerce industries can be analysed to identify the actants in this scenario. The cloud technology services help to bring a lot of advancements in the performance and productivity of e-commerce businesses (Gong and Xu, 2014). From A.N.T. perspective, the actants are categorized as technological and social actants. The cloud-based services provided by Amazon, ERP cloud applications; Amazon Virtual Private Cloud (VPC), etc are depending on the technical actants such as software, hardware, data storage, platform infrastructure, SaaS, Paas, IaaS and other related cloud services. A.N.T. analyses and researches the way by which e-commerce can face the challenges brought by the era of cloud computing. Cloud-based computing services have greatly influenced electronic or digital marketing. The critical factors of e-business are being operated on by the technical components that result in a positive effect and improvement of sociological aspects. The models of business are hugely expanded; as a result, smart speedy and quick online transaction take place nowadays. Business is transforming and taking up a new form to incorporate a larger number of emerging technologies, increasing revenues with an easiness of spreading worldwide and conducting business without any geographical or time barriers (Withers, 2004).

Big Data Analytics has been able to give the organizations solutions to manage the large pool of data in an efficient manner. Bharti Airtel database has managed to handle new customers amounting to some 1.5 million each month efficiently. A case study made in 2014 by Vodafone and Argyle Data that comes under the Telco Innovation Case Studies, has been able to draw the tremendous positive effects of deploying big data in variety of fields such as preventing network fraud and misuse of data (Han, 2015).

Analysing the interrelationships and interactions within the big data networks from ANT perspective involves identifying the underlying actants that are acting upon the whole system or process. These actants can be categorised as human and non-human actants. In order to explore further, the technological actants are identified as the software and hardware actants and it includes the data management mechanisms, networking measures, data transmission channels, database access software and the “pool of data” (Huang and Zhang, 2014). The non-human actants altogether affect the social aspects of computing. The highly complex volume and granularity of a large number of fields big data has been applied to (e.g. data mining and data linking). The assemblage of computing theory inspects the way data and knowledge based on a subject can be turned into expertise and how data can command a social and material value. The roles of actants on big data vary from social networking sites such as Facebook and Twitter as well as a vast range of platforms operating on big data analytics (Jackson, 2013). These actants play distinct roles in the society by interacting with the human actors i.e. the database users, large business organisations using big data technology, customers and consumers, common end-users of social networking sites or employees belonging to a company operating on big data components.

Conclusion

Modern day computing technologies are the latest in the long history of technology that develops our way of living and nurture our social life being implemented in the network. Despite the fact the world being grasped by emerging technologies we can have a clear scenario that this modern computing technology plays a major role in the assemblage of computers to social networks (Shen and Qian, 2014). The social media, customers, business entities play major roles as actants to evaluate the effects of modern computing on the social, cultural as well as political paths of life. Based on the story, the theory of actor-network was suitable under these circumstances for analysis and depicts to accomplish the objectives of the conversation.

Reference List

Bernstein, D. (2015). Is Amazon Becoming the New Cool Software Company for Developers?. IEEE Cloud Comput., 2(1), pp.69-71.

Duan, L. and Xiong, Y. (2015). Big data analytics and business analytics. Journal of Management Analytics, 2(1), pp.1-21.

Gong, S. and Xu, J. (2014). Electronic Commerce Personalized Recommendation Model under Cloud Computing Environment. AMM, 513-517, pp.639-642.

Han, Y. (2015). Cloud storage for digital preservation: optimal uses of Amazon S3 and Glacier. Library Hi Tech, 33(2), pp.261-271.

Huang, L. and Zhang, X. (2014). Research on Development Mode of E-Commerce Based on Cloud Computing. AMR, 889-890, pp.1288-1291.

Jackson, K. (2013). OpenStack Cloud Computing Cookbook. Birmingham: Packt Publishing.

Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2015). An Efficient Time Optimized Scheme for Progressive Analytics in Big Data. Big Data Research.

Newcombe, C., Rath, T., Zhang, F., Munteanu, B., Brooker, M. and Deardeuff, M. (2015). How Amazon web services uses formal methods. Communications of the ACM, 58(4), pp.66-73.

Shen, Y. and Qian, Y. (2014). A Study of New E-Commerce Logistics Mode Based on Cloud Computing Technology. AMR, 1049-1050, pp.1848-1852.

Singh, D. and Reddy, C. (2014). A survey on platforms for big data analytics. Journal of Big Data, 2(1).

Withers, C. (2004). Review: Google, Amazon, and Beyond: Creating and Consuming Web Services. The Computer Bulletin, 46(5), pp.30-30.

Xue, N. and Chang, L. (2014). Design Tradeoffs in Applying CAS to File System Backed by Amazon-S3. AMM, 543-547, pp.3423-3426.

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