- Python Social Media Analytics
- Siddhartha Chatterjee Michal Krystyanczuk
- 235字
- 2021-07-15 17:24:50
Delving into social data
The data acquired from social media is called social data. Social data exists in many forms.
The types of social media data can be information around the users of social networks, like name, city, interests, and so on. These types of data that are numeric or quantifiable are known as structured data.
However, since social media are platforms for expression, a lot of the data is in the form of texts, images, videos, and such. These sources are rich in information, but not as direct to analyze as structured data described earlier. These types of data are known as unstructured data.
The process of applying rigorous methods to make sense of the social data is called social data analytics. In the book, we will go into great depth in social data analytics to demonstrate how we can extract valuable sense and information from these really interesting sources of social data. Since there are almost no restrictions on social media, there are lot of meaningless accounts, content, and interactions. So, the data coming out of these streams is quite noisy and polluted. Hence, a lot of effort is required to separate the information from the noise. Once the data is cleaned and we are focused on the most important and interesting aspects, we then require various statistical and algorithmic methods to make sense out of the filtered data and draw meaningful conclusions.
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