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Social Media Data Mining and Analytics by Antonios Chalkiopoulos, P. Oscar Boykin, Gungor Polatkan, Gabor Szabo

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CHAPTER 7Conclusions

In the preceding six chapters of the book, you looked at various aspects of social media systems by analyzing data collected from these services. To put it another a way, social media enables you to see how people interact with each other, how they consume and produce content, and what kinds of connections they form with others while doing so. Social media is only the vehicle by which you can observe all these activity patterns. Before the advent of social media, it is likely that people were interacting with each other and their environment in similar ways as they are doing now with the help of an online service. The goal of this chapter is to briefly recap what you have learned about such observations because the commonalities will probably be applicable to any social media system that revolves around human users and relies on their activities.

The Surprising Stability of Human Interaction Patterns

Now review the main characteristics of social media services and human behavior that you have learned in this book.

  • Activity patterns: In Chapter 1 you learned that the number of times individual users engage in some kind of an activity is usually governed by a long-tailed (power-law) distribution. Many users are active just a few times during a given period, whereas a few of them are active an unexpectedly large number of times. The number of such highly active users is small, but not as small as conventional wisdom might suggest: There are enough users ...

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