Summary:
This paper talks about how a classifier was trained in order to distinguish twitter accounts in different categories. These categories consisted of organizations, journalists/bloggers, and consumers. They were able to define these groups using the Welch and Kolmogorov-Smirnov t-test. His findings were very interesting, organizations tended to be more professional while journalists use more of a personal style. Organizations also tend to share a lot more links than journalists.
Reflection:
One of the first things that popped out at me was the fact the organizations seems to be a lot more reserved than journalists. If you think about it, it makes a lot of sense, I’m going to use buzzfeed as an example because that is a website I follow closely. Buzzfeed as an organization probably does not want to be tied to certain political views or ideologies that could deter potential consumers from using their site or purchasing merchandise. Whereas, a journalist for buzzfeed can much more freely tweet their opinion online without drawing attention to the company as a whole if they do so on their private twitter account. Similarly the statistic that organizations have 3 times the number of links posted than journalists is likely tied to this as well. Buzzfeed wants to advertise the company on platforms like twitter but doesn’t care about using twitter as a form of information distribution. They post links directing consumers to their official website where information/blogs/videos are posted for the user to see. On the other hand, journalists will probably use sites like twitter to publish their personal opinion on a subject matter without linking anything.
Another big discrepancy between journalists and organizations is that they use different mediums to publish their tweets. For journalists, they seem to primarily use their phones which does not surprise me at all. If we go back to my previous example about a buzzfeed journalist, if most of the time it is just a quick statement about your opinion on a matter than there is no need to use anything other than your phone. With a phone, they also have the capability to tweet wherever and whenever they want. Organizations use special twitter applications a lot more than a journalist. This also makes sense to me, from my experience at the biomedical high-performance computing lab at Virginia Tech they would often scheduled their tweets so that there would be daily tweets at common peak times. As an organization they must make sure that they’re coming out with steady content to keep their consumers engaged. This would also explain why journalists tend to reply to their readers more than an organization. While a journalist has their phone on them almost all the time, organizations often don’t check their replies they just use Twitter as a platform to advertise their company and recent posts on their official website.
Future Work:
This article is really interesting to me because I am hoping to use data analytics to find misinformation within the news. I wasn’t exactly sure where to start however it’s helpful to know that we can distinguish different types of users based off their posting and replying habits.
I do have a few additional questions that this work could answer in the future.
- First what features would we be able to use to distinguish different types of organizations, for example Wendys from CNN, if given a big dataset of organization information? Word association seems to be a good start but are there better solutions?
- How could we differentiate organizations like Wendys that reply to their readers and do not post links often without mislabeling them as a journalist?
- How would the features be discovered for finding misinformation from these sources whether they are a journalist or organization?
