Now that we’ve taken a fairly generic look into how social media data is collected, we can look into how their analysis process differs between commercial and academic purposes.
One of the most important aspects of using Twitter data in a commercial business context is strictly adhering to the platform’s API (application programming interface) terms of service. If all is done inhouse by a commercial organization for its own use, there is less to worry about; however, for a third-party organization that analyzes Twitter as its business model, it must deal with specific rules. For example, sharing Twitter content including datasets of text and following relationships are not allowed. It is important to analyze the information in a derivative way, like the number of Tweets that had a negative sentiment.
3.5.1 Business Approach
Businesses have specific goals for taking advantage of social media information. Some use it in-house for their own needs, and others offer their analyses as a service.
IBM is one business that has taken to social media metrics very rapidly, and they have blogs and tools used to leverage social media. As one of their business models, they offer business-to-business solutions. Currently IBM offers “social merchandising” for retail and consumer products using Twitter data, but they are working to provide market insights for these areas, as well as for media and entertainment [30].
In IBM’s big data hub, they describe the ways other retailers can use big data [31]:
- To predict what customers want before they ask for it
- Fix issues as they occur in real-time
- Discover and resolve common and reoccurring problems
3.5.2 Academic Approach
Academia uses social media data to promote and share findings and research, similarly to how any other organization might promote itself publicly. On the other hand, for academics, social media has become essential for other research. Instead of viewing the information as a source to guide business direction, academic use would focus more on the inherent knowledge gained from the data, rather than commercial gains.
In Section 3.6, we will look at case studies of academic research on disease and health via social media, but it’s also important to know how these projects come about. The time and work put into academic research projects are not free. Time is essentially money, and it also costs money to pay talented workers to help design and implement a big data project. One source of this money comes through grants, and many social media platforms offer grants to keep academics involved. For example, Twitter has offered grants before, especially because of the significant insights the research offers, like where influenza is likely to strike [32].