To Be or not to Be on Social Media: Analysis Using Tragedy of Commons
The advent of the internet has drastically changed human lives. Social media websites like Facebook, Twitter, Instagram, etc. are being used by millions of people worldwide daily. Consequently, such websites have become a treasure trove of data. Even today, people have not been able to fully compreh...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Madhura Ranade [verfasserIn] Aniruddha Joshi [verfasserIn] Neha Patvardhan [verfasserIn] Paritosh Bedekar [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Persisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Iranian Journal of Information Processing & Management - Iranian Research Institute for Information and Technology, 2013, 38(2022), 1, Seite 19-42 |
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| Übergeordnetes Werk: |
volume:38 ; year:2022 ; number:1 ; pages:19-42 |
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The advent of the internet has drastically changed human lives. Social media websites like Facebook, Twitter, Instagram, etc. are being used by millions of people worldwide daily. Consequently, such websites have become a treasure trove of data. Even today, people have not been able to fully comprehend the consequences, both positive and negative, of being on these websites. We have modelled the risks associated with such websites as a function of the population, i.e., the number of accounts present, along the lines of the tragedy of commons. We have tracked the variations between the average Strogartz Watts local clustering coefficient, the variance of Strogartz Watts local clustering coefficient and the global clustering coefficient as the number of accounts in a database increase. With regards to the average local and global clustering coefficient, researchers observed that there is an initial phase of rapid increase followed by a phase of a continuous relatively smaller increase in their values. The variance of the average local clustering coefficient shows an initial phase of significant variation followed by a phase of continuous reduction in its value. Thus, the increase in the population size increases the transitivity of the network, increasing the risk associated with data being leaked via the website. |
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The advent of the internet has drastically changed human lives. Social media websites like Facebook, Twitter, Instagram, etc. are being used by millions of people worldwide daily. Consequently, such websites have become a treasure trove of data. Even today, people have not been able to fully comprehend the consequences, both positive and negative, of being on these websites. We have modelled the risks associated with such websites as a function of the population, i.e., the number of accounts present, along the lines of the tragedy of commons. We have tracked the variations between the average Strogartz Watts local clustering coefficient, the variance of Strogartz Watts local clustering coefficient and the global clustering coefficient as the number of accounts in a database increase. With regards to the average local and global clustering coefficient, researchers observed that there is an initial phase of rapid increase followed by a phase of a continuous relatively smaller increase in their values. The variance of the average local clustering coefficient shows an initial phase of significant variation followed by a phase of continuous reduction in its value. Thus, the increase in the population size increases the transitivity of the network, increasing the risk associated with data being leaked via the website. |
| abstract_unstemmed |
The advent of the internet has drastically changed human lives. Social media websites like Facebook, Twitter, Instagram, etc. are being used by millions of people worldwide daily. Consequently, such websites have become a treasure trove of data. Even today, people have not been able to fully comprehend the consequences, both positive and negative, of being on these websites. We have modelled the risks associated with such websites as a function of the population, i.e., the number of accounts present, along the lines of the tragedy of commons. We have tracked the variations between the average Strogartz Watts local clustering coefficient, the variance of Strogartz Watts local clustering coefficient and the global clustering coefficient as the number of accounts in a database increase. With regards to the average local and global clustering coefficient, researchers observed that there is an initial phase of rapid increase followed by a phase of a continuous relatively smaller increase in their values. The variance of the average local clustering coefficient shows an initial phase of significant variation followed by a phase of continuous reduction in its value. Thus, the increase in the population size increases the transitivity of the network, increasing the risk associated with data being leaked via the website. |
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To Be or not to Be on Social Media: Analysis Using Tragedy of Commons |
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