The practise of acquiring and evaluating data from social networks like Facebook, Instagram, LinkedIn, or Twitter is known as Social Media Analytics. Social media monitoring, often known as social listening, is a component of social media analytics. Marketers frequently use it to monitor internet discussions of products and businesses. It is "the art and science of extracting significant hidden insights from enormous amounts of semi-structured and unstructured social media data to enable informed and intelligent decision making," according to one author. Social Media Analytics involves three primary stages: data identification, data analysis, and information interpretation. Analysts may provide a question that has to be addressed in order to optimise the value gained at each stage of the process. Who, What, Where, When, Why, and How are crucial inquiries for data analysis. These inquiries assist in selecting the appropriate data sources to assess, which may influence the kind of research that may be carried out. The process of selecting the subsets of accessible data to concentrate on for analysis is known as data identification. When raw data is interpreted, it becomes helpful. Data can start to communicate a message after analysis. Information is any data that provides a valuable message. Unprocessed data can be translated into exact message in the following ways: noisy data; relevant and irrelevant data that has been filtered; only relevant data; data that conveys a vague message; knowledge; data that conveys a precise message; wisdom; and data that conveys the exact message and the reasoning behind it. We need to start processing unprocessed data, refine the dataset by adding the data we want to focus on, and organise data to find information before we can gain knowledge from it. Data identification in the context of Social Media Analytics refers to "what" content is interesting. Along with the content text, we also need to know who wrote it. Where did it turn up, and which social media platform? Are details from a particular region of interest to us? When was something posted on social media? How can we tell if the evidence is strong enough to support a claim? We have no idea, is the correct response. If we don't start looking at the data, we won't know this. If we discovered that the data is insufficient, we should repeat the first step and change the question. If the data are deemed adequate for analysis, we must create a data model. To organize data items and standardize how they relate to one another, we utilize a process or procedure called developing a data model. This step is critical because we want to run a computer program over the data; we need a way to communicate to the computer which terms or themes are crucial and whether specific terms are relevant to the subject at hand.
0 Comments
Leave a Reply. |
Categories
All
|