Social media as an Internet innovation and the metric identification

This blog includes mainly two parts which covers the discussion of social media as an Internet innovation and the discussion of metric identification with the reference to its evolution in China as well as how it should or should not be applied in Australia.


Part one

The start of social media should be dated back to the sending of the first e-mails from intellectuals in ARPA (the Advanced Research Projects Agency) in 1971 which signals the arise of people networking through Internet (Peters et al., 2013). Then, in 1980, the introduction of USENET enabled users to read and posted information involving science, music and literature on the billboard. In 1991, Justin Hall opened his own website to record on his own life and stories which is regarded as the first emergence of individual blog in the history of Internet (Collins et al., 2013). Then in 21st century, with the introduction of websites like Meetup and Myspace, people began to socialize and connect to each other through Internet.


Source: ( 2012, Ifanr, The evolution of social networking)



Tools like Meetup and Myspace as well as Facebook and Twitter are called platforms. It is the use of these platforms that transforms people’s way of networking by breaking up existent social boundaries (Becher et al., 2010). As for the differences between social networking service and social media, the major aim of social networking services is to connect and contact between users, such as Tinder and Grinder while for social media, information and life style sharing would be the main output of users with the use of contacting being minimized (Bertrand, 2013).




Source: ( 2012, Ifanr, The evolution of social networking)


When it comes to the organization which dominates the industry of social media, the controller of key businesses differs in China and in Western world. Facebook, Twitter and Instagram would be mostly used in Western world while wechat, weibo, QQ and DouYin.


The advent and spread of social media have undoubtedly brought tremendous influence to the world in different aspects such as political, economic and social aspects.


  1. Political

Compared with other media, the influence of social media in political movement has greatly increased. 62% of people claimed to have acquired news from social media in a research conducted by Pew research centre. Social networks are playing an increasingly important role in electoral politics – first, in 2003, when Howard Dean failed to win the election, and then in 2008 he was elected the first African American president.


Source: ( Sohu, 2020, How is social media changing the world?)

“The election of Donald J. trump is perhaps the most striking example to date of the fact that social networks are helping to fundamentally reshape human society on a global scale,” the New York Times reported. As social media allows people to communicate more freely, they are helping to create social organizations with unexpected influence in marginalized groups (Collins et al., 2013).


  1. Economic

The rise of social media means that organizations would be able to attract its customers and potential customers through one or more social media platforms, which help companies recognize the importance of using social media to connect with customers and increase revenue (Haustein et al. , 2015). Companies have realized that they can use social media to generate insights, stimulate demand and create targeted products. This is important in the traditional physical car business, and obviously in the e-commerce world.


Source: ( Sohu, 2020, How is social media changing the world?)

Many studies have shown that implementing social networks in the workplace can enhance knowledge sharing. The result is improved project management activities and the dissemination of expertise. Full implementation of social technology in the workplace eliminates boundaries, eliminates islands, promotes interaction and helps create more skilled, knowledgeable workers (Moussa, 2019).


However, the disadvantage for the adoption of social media would be that the small number of social “shares” will lead to negative social evidence and damage corporate reputation. A research from found that after deleting the share button from the product page, the conversion rate increased by 11.9% (Wu et al., 2011). These results highlight the double edge of the impact of social media. When a product attracts a large share, it can promote sales. But when the opposite happens, customers start to distrust the product and the company (Wu et al., 2011).


  1. Social

Currently, nearly a quarter of the world’s population are using Facebook. In the United States, nearly 80% of Internet users use the platform. Because social network lives on the interaction between people, with the development of social network, social network becomes more and more powerful (Collins et al., 2013).


Without social media, social, moral, environmental, and political abuses will do nothing. The increased visibility of the problem has shifted the balance of power from a few people to the masses. social media is slowly eliminating real activism and replacing it with “relaxationism” (Collins et al., 2013).


Part Two

Biometric is a technology that combines computer with high-tech means such as optics, acoustics, biosensors and biostatistics, and uses the inherent physiological characteristics of human body to conduct personal identification (Mukhra et al., 2018). Biometrics mainly include fingerprint recognition, speech recognition, face recognition, iris recognition, etc.


In the era of information and technology, biometric technology is emerging gradually because of the shortcomings of traditional password, such as easy to lose, easy to forget and not bound to users, and become an important means of identity verification instead of traditional password recognition (Mukhra et al., 2018).


Source: (Filecombo, 2018 “The variety of metric identification)


With the rapid development of the Internet, the application of biometrics has also increased rapidly in China. The most common applications include fingerprint payment, fingerprint login, voice start, iris scanning.


Despite of the convenience brought by biometrics identification; its disadvantages could not be neglected as well.


  1. Transmission risk.

In the Internet environment, biological identification must be converted into digital identification, and then transmitted through the network (Mukhra et al., 2018). As other network applications, transmission process is faced with the risk of leakage, which reduces the level of security. From this point of view, it is the same as the general password, and it is not different in security.


Source: (Qianzhan, 2017, The outlook for metric identification)

  1. Irrevocability.

The biggest disadvantage of biometric is its irrevocability. In short, if users find a password at risk, they can change it immediately (Mukhra et al., 2018). But if users’ fingerprint, iris, face scan is stolen, you can hardly undo or recover. It will become an organ of you on the Internet, and it will be sold and sold in packages; organizations and hackers in all corners of the world will analyze, use and consume it from various perspectives (Mukhra et al., 2018).


  1. Accuracy and uniqueness.

At present, many biometric applications call it to be accurate to a new height. This is not entirely true, or accuracy does not represent its security. For example, the daily use of mobile phone fingerprint login, which generally only needs part of the fingerprint of the finger to log in, which would cause a problem, that is, when there are multiple biometric verification points, only part of the verification points are needed to complete the verification, which will inevitably lead to the uncertainty of uniqueness (Mukhra et al., 2018).


Therefore, considering the shortcoming as well as the merits of metric identification, the introduction of it into Australia would bring both benefits and risks. Firstly, considering the weak foundation of metric identification in Australia, it would be both money and time consuming to introduce the technology. Secondly, as it is mentioned above, metrics identification has brought new discussion on the issue of personal information security, which would also be the major concern when introducing to Australia. However, it is no doubt that the accuracy and the convenience of the technology would also enable the reform of identification in Australia.


In this way, it would be beneficial to introduce the technology, yet, how to do the introduction and how would it be promoted to the public in Australia should be conducted with more deliberation.



Aljukhadar, M., Senecal, S., & Bériault Poirier, A. (2020). Social media mavenism: Toward an action-based metric for knowledge dissemination on social networks. Journal of Marketing Communications, 26(6), 636-665.

Becker, H., Naaman, M., & Gravano, L. (2010). Learning similarity metrics for event identification in social media. In Proceedings of the third ACM international conference on Web search and data mining (pp. 291-300).

Bertrand, G. (2013). Social media research: developing a trust metric in the social age. International Journal of Market Research, 55(3), 333-335.

Chen, G., Kong, Q., & Mao, W. (2017, July). Online event detection and tracking in social media based on neural similarity metric learning. In 2017 IEEE International Conference on Intelligence and Security Informatics (ISI) (pp. 182-184). IEEE.

Collins, C., Hasan, S., & Ukkusuri, S. V. (2013). A novel transit rider satisfaction metric: Rider sentiments measured from online social media data. Journal of Public Transportation, 16(2), 2.

Haustein, S., Costas, R., & Larivière, V. (2015). Characterizing social media metrics of scholarly papers: The effect of document properties and collaboration patterns. PloS one, 10(3), e0120495.

Moussa, S. (2019). An emoji-based metric for monitoring consumers’ emotions toward brands on social media. Marketing Intelligence & Planning, 46(9), pp. 12-27.

Mukhra, R. , Krishan, K. , & Kanchan, T. . (2018). Bare footprint metric analysis methods for comparison and identification in forensic examinations: a review of literature. Journal of Forensic and Legal Medicine, 101-112.

Wu, P., Hoi, S. C. H., Zhao, P., & He, Y. (2011, February). Mining social images with distance metric learning for automated image tagging. In Proceedings of the fourth ACM international conference on Web search and data mining (pp.197-206).