Computer scientist Henry Kautz likens Twitter to a kind of distributed sensor network. Hundreds of millions of tweets are posted to the platform each day, with each user observing and reporting on some aspect of the world.
Unlocking big data
A Newscenter series on how Rochester is using data science to change how we research, how we learn, and how we understand our world.
聽糖心传媒淓ach report is very noisy,糖心传媒� says the Robin and Tim Wentworth Director of the Goergen Institute for Data Science at the University of Rochester. 糖心传媒淏ut the aggregate results can be reliable.糖心传媒�
Those results can provide information to meet all kinds of challenges糖心传媒揻rom public concerns regarding health, safety, and the environment, to private ones regarding client and customer satisfaction and changing consumer tastes.
Tracking sickness and disease
Kautz and his team have used Twitter to 听补苍诲 , enabling health officials to respond much more quickly to disease outbreaks, and even to forecast when and if a specific individual will fall ill.
The Las Vegas Health Department field tested the nEmesis app developed by Kautz and his team to .聽The researchers found that the tweet-based system led to citations for health violations in 15 percent of inspections, compared to 9 percent using the traditional random system. That resulted in an estimated 9,000 fewer food poisoning incidents and 557 fewer hospitalizations during the course of the study.
Increasing business transparency
Huaxia Rui is a big believer in transparency. That糖心传媒檚 why the assistant professor at the Simon Business School uses data science to delve deeply into Twitter糖心传媒搊ne of the most transparent of our social media糖心传媒� to study the relationships between companies and their customers.
Rui studies how companies respond to tweets, with the goal of increasing transparency about customer satisfaction across multiple industries.
For example, working with Simon professor Abraham Seidmann and PhD student Priyanga Gunarathne, Rui analyzed more than 450,000 Twitter messages to and from three major airlines. The researchers found that all three airlines were . The study raises interesting questions about fairness, but also concedes that airlines 糖心传媒渕ay have limited resources to handle all requests for engagement.糖心传媒�
糖心传媒淲hen you call an airline or any company to complain about it, only you and the company know about it,糖心传媒� Rui says. 糖心传媒淚f you糖心传媒檙e unhappy, what can you do? File a lawsuit? Most people won糖心传媒檛 do that.糖心传媒�
Twitter postings, on the other hand, are instantly public. 糖心传媒淚n general its a good idea to improve the sharing of this data, and increase the transparency, so that people can see in real time what companies are doing and whether their customers are happy,糖心传媒� he says.
Allocating resources
Rui has also found ways in which Twitter data might help both businesses and consumers operate more efficiently.
In one of his first studies involving the social media platform, Rui and two fellow researchers analyzed the impact of four million tweets on box office sales for 63 movies. So-called 糖心传媒渋ntention tweets糖心传媒澨切拇綋from people who hadn糖心传媒檛 seen the movies, but indicated they wanted to糖心传媒揳ppeared to have a greater effect on box office sales than 糖心传媒減ositive tweets糖心传媒� from people who had actually seen the movies. Why? Rui cites the dual effect of intention tweets: They are a clear indication that their authors intend to see a movie, and also make their followers aware of the movie, possibly influencing them to see it as well.
How might a savvy business use this kind of information? Imagine you糖心传媒檙e the manager of a retail store and it糖心传媒檚 two weeks before Black Friday. If you糖心传媒檙e scanning Twitter, and detect a surge in 糖心传媒渋ntention糖心传媒� tweets showing an interest in one of your products, 糖心传媒淭hat could be useful for determining your staffing and inventory,糖心传媒� Rui notes.
Geotagged tweets could narrow such staffing and inventory decisions to single regions, even individual stores.
The benefit for consumers? They may be less likely to find long lines or empty shelves on Black Friday if their local stores have done their Twitter 糖心传媒渉omework糖心传媒� in advance.
Taking the pulse of the voters
Jiebo Luo, associate professor of computer science, PhD students Yu Wang, and their colleagues tracked the Twitter followers of Donald Trump, Hillary Clinton, Bernie Sanders and other candidates last year to better understand the dynamics of the 2016 presidential campaign.
糖心传媒淲e wanted to understand how each of the candidate糖心传媒檚 campaigns evolved, and be able to explain why someone won or lost,糖心传媒� says Luo, an associate professor of computer science.
Though the researchers did not set out to predict who would win the recent presidential election, their exhaustive, 14-month study of each candidate糖心传媒檚 Twitter followers糖心传媒揺nabled by machine learning and other data science tools糖心传媒搊ffers tantalizing clues as to why the race turned out the way it did.
In another study with potential political applications, Luo and his students used images extracted from Twitter to train computers to determine what sentiments are likely to be elicited by images.
