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Signed Networks in Social Media

With social media being a big force in modern virtual and non-virtual relationships, there are some interesting analyses done on the signed networks that exist within the platforms. In the article titled Signed Networks in Social Media, the three researchers Jure Leskovec, Daniel Huttenlocher, and Jon Kleinberg, take a look at the network representations of 3 online platforms Epinions, Slashdot, and Wikipedia. Epinions, an ecommerce platform, Slashdot, an online social news website, and Wikipedia, the online encyclopedia all incorporate aspects of a positive/negative relationship for their users.

On Epinions, users can give ratings not only to the items sold on the marketplace, but also to other users on the site as well. On Slashdot, users can label other users as ‘friends’ or ‘foes’. Wikipedia periodically has volunteer candidates considered for a promotion into an admin role on the platform, and the community casts public votes for whether they are for or against this promotion.

The table below shows the data for the signed relations within these networks. These figures show that for weak structural balanced networks, triangles with two positive edges are massively underrepresented. Triangles with three positive edges are overrepresented when compared to the other types of triangles.

The data from these 3 platforms give further developments for signed networks. For triangles within signed networks, we label balanced triangles as triangles with an odd number of positive edges. Balanced signed network analysis is usually applied to undirected networks. This is where the ideas of “the friend of a friend is a friend”, and “the friend of my enemy is my enemy” came from. An idea that is explored in this paper is the theory of status, which has applications in directed networks. Status in signed networks indicate that the creator of positive links view the recipient of the relationship as having higher status, and the creator of negative links view the recipient of the relationship as having lower status. A good way to distinguish between these two theories is their proposed situation: A links positively to B, B links positively to C, according to the balance theory, A should link positive to C as well as C is a friend of a friend. However, in the status theory, since C > B > A, C should view A as having lower status in the hierarchy.

Since social media and many of these online platforms tend to be used for personal satisfaction, such as finding interests or a community to belong to, it makes sense that positive triangles are overrepresented. People tend to dislike being involved with online conflict, as many internet celebrities nowadays are constantly being very cautious in order to have a good public image. It is also relevant to average users as well, people want to maintain good relations and a good public image to their fellow friends on these platforms. On websites like Linkedin, keeping good connections and avoiding creating bad ones are important, as having more of a positive profile opens up many more job opportunities.

Social media is an entity that has now been decades old, and is built on the relationships of its users. These analyses done on the networks between the relationships on these platforms can teach us the trends between how users use their service, and additional data collected can even further improve the user experiences for everyone around the world.

Source:

https://cs.stanford.edu/people/jure/pubs/triads-chi10.pdf

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How The Pandemic Changed The Way We Use The Internet

With the recent pandemic, people are forced to be confined to their homes much more than before. Self isolation to prevent the spread of the virus by the population caused a drastic change in many peoples’ lives, especially the lives of people who are very used to going outdoors for entertainment. This unprecedented and abrupt change in lifestyle impacted the lives of many people. People working at home, the reliance on deliveries in order to avoid human contact, the pandemic has shaped our world to force us to be able to live by ourselves.

As a result of more people flocking online for entertainment, this confinement changed how people used the internet. According to the New York Times, Facebook saw a 27% increase, Netflix saw a 16% increase, and YouTube saw a 15.3% increase in users on their already massive userbase.

Obviously with social media platforms such as Facebook and Twitter, its average daily users along with the businesses that run a page had to change how they managed these platforms as well. The coronavirus led to significant discussions online. Roseman University of Health Sciences conducted a research on these discussions, and suggests that understanding these discussions can help institutions, governments, and individuals navigate themselves during the pandemic. Their method of research implemented AI to analyze Twitter data in the United States from March 20th to April 19th of 2020, and mainly focused on COVID-19 discussions.

The following figure shows the social network graphs of topics with a dominant influence, along with the top 10 words that associated with the topic. The node size per word is proportional to the weight of the edges connected to it. The analysis shows that among the 5 topics, the closeness centrality measure is highest for emotional support, indicating that it is likely associated with each of the other discussions.

The discussion of mental health is important during this period of time, as the feeling of isolation and loneliness is hugely amplified in those who are not used to this style of living. As social media is known to create echo chambers and bubble type communities, the negative effects of social media use was also amplified.

The following heatmap shows the average sentiment score of the states in the country. Darkness of the state colors associated with negative sentiment scores, and lighter colors associated with positive sentiments scores.

Their research done indicated that positive sentiment outweighed negative sentiment. Public sentiment data is important to the efforts towards the coronavirus relief, and can help guide government workers and businesses with information allowing them to make impactful decisions.

What we can take away from these results is that adapting to an issue of this scale is very difficult. The pandemic’s impact on the healthcare sector in every country is immense, and the timing could not have been worse for the global economy. People now need more emotional support than ever, and the social changes that resulted from this forced the population to find new ways to interact with peers and loved ones. With the grimness of the statistics of the pandemic, and increased stress from the uncertainty of how the situation is, people can only hope for things to get better. But with the capabilities of technology and scientists today committing to a cure and solutions to the many problems, we can have faith that everyday life will go back to normal soon.

Sources:
https://www.nytimes.com/interactive/2020/04/07/technology/coronavirus-internet-use.html

https://www.jmir.org/2020/8/e22590/