Hello Manoj Kumar Srivastav ,

Homophily is a principle in social networks that states that similar people are more likely to be connected to each other than dissimilar people. This can be observed in many different types of social networks, such as friendships, social groups, and professional networks.

There are several factors that can contribute to homophily. One factor is social similarity, which refers to the tendency for people to be friends with others who share similar interests, values, and backgrounds. Another factor is structural similarity, which refers to the tendency for people to be friends with others who are located in close proximity to them. Finally, status homophily refers to the tendency for people to be friends with others who have similar social status or prestige.

Homophily can have a number of important consequences for social networks. One consequence is that it can lead to the formation of homophilous subgroups, which are groups of people who are very similar to each other. These subgroups can be very strong and cohesive, but they can also be exclusionary and resistant to change.

Another consequence of homophily is that it can lead to information cascades or content getting viral, which are processes in which information spreads rapidly through a network from one person to another. Information cascades can be helpful in spreading important information, but they can also be harmful if they spread misinformation or harmful rumors.

There are a number of datasets available for studying homophily in social networks. Some of these datasets include:

• The Facebook100 dataset, which contains data on over 100 million Facebook users and their relationships.
• The KONECT dataset, which contains data on over 1.8 billion social media interactions.
• The Human Connectome Project dataset, which contains data on the brain connectivity of over 1,200 people.
• The Pandemic Social Connectedness Project dataset, which contains data on the social connections of over 15,000 people during the COVID-19 pandemic.

These datasets can be used to study a variety of aspects of homophily, such as the different types of homophily that exist, the factors that contribute to homophily, and the consequences of homophily for individuals and society.

Hope this helps!

Regards,

Dr. Nitin Saini.

Nitin Saini Not sure why you signed your name to something written by an AI.

Dear Manoj Kumar Srivastav ,

Homophily is a well-established phenomenon that has been observed to occur frequently in social networks, where users with similar contexts have a nature of connecting with one another constantly, and this principle is also a meticulously thought-out field in the domain of social sciences

https://arxiv.org/pdf/2008.10383.pdf

Regards,

Shafagat

Please read it: https://www.futurelearn.com/info/courses/social-media/0/steps/16055

How mathematical or machine learning approach will be implemented with respect to Homophily?