Big Data Analytics Lab

Publications through the Lab

  1. *bold fonts indicate student co-authors from the lab

Big Data Analytics Lab Wikipage: We accumulate our knowledge in this wikipage (created by Mary Falling)

Our Team

Github: All the major scripts and data produced by the lab are stored and updated in this github under proper category.

We use big data to solve real world problems. Current projects are about crisis communication during emergency, citizen service requests about infrastructure during natural disaster such as hurricane. Big data analytics enable data driven decision making by leveraging the power of big data.

Current Students (2025):

Alina Hagen, Christopher Reddish, and Daniel Tafmizi (Undergraduate BSIS, Data Science and Analytics Concentration, USF)

Faculty Collaborators:

Previous Students:

  • Diego Ford and Jahnae Edwards (Undergraduate BSIS, Data Science and Analytics Concentration, USF)
  • Barbara Howe (Ph.D. student, USF)
  • Robert Moncrief (Undergraduate BSIS, Data Science and Analytics Concentration, USF)
  • Lilith Holland (Undergraduate BSIS, Data Science and Analytics Concentration, USF)
  • Steven Horton (Revenue Management Solutions, Business Insights Analyst, BSIS with Data Science and Analytics Concentration, USF)
  • Deaundre Dyson (Undergraduate BSIS, Data Science and Analytics Concentration, USF)
  • Tuc Chau (Ph.D student, Linguistics, USF)
  • William Webb (Ph.D student, Anthropology, USF)
  • Mihir Patel (Current: data analysis graduated with BSIS, Data Science and Analytics Concentration, USF)
  • Wesley Gardiner (Current: Ph.D. student at USF graduated with BSIS, Data Science and Analytics Concentration, USF)
  • Mary Falling (Current: data analyst, graduated with MSIS, USF)
  • Jermaine Covington Jr. L. (BSIS, USF)
  • Amy Bryant (Software Engineer at Kin Insurance graduated with MS LIS, USF)
  • Justin Costakis (Current: Intelligence analyst, Citi)
  • Ryan Scharf (Current: American Integrity Insurance, BSIS in Data Science and Analytics )
  • Hye Seon Yi (Current: Ph.D. Student at Computer Science Engineering, USF)
  • Siana Pietri (Current: National Security Agency, MSIS)
  • Oleksandr Lisnichenko, Pankti Mehta (Honors College, USF)

Funded Project: Social Bots and Disinformation in Cyber‐Discussions of COVID19

COVID‐19 and Cybersecurity Research Initiative, Hagen (PI), 06/01/20-09/31/20 $42,000: The goal of this study is to examine the spread of information (including factual information, misinformation, and disinformation) in social network discussions of COVID19. The findings will aid in identifying and countering disinformation, as well as deepening our understanding of the role that social bots play in these activities.

Publications

2020 “Social Media Use for Crisis and Emergency Risk Communications During the Zika Health Crisis” Digital Government: Research and Practice

Many public officials and government agencies are facing increased pressure to utilize social media as a crisis communications tool. However, significant questions remain unanswered regarding how social media can be best leveraged to facilitate effective communication efforts under crisis conditions. These questions are often more challenging for local government agencies, where unsupportive culture and a lack of resources tend to discourage the active use of social media in governing. In an effort to better inform these discussions, this article examines the use of Twitter by federal, state, and local government actors during the 2015–2016 Zika virus outbreak in the United States. The findings show that local governments have smaller network sizes, on average, than their state and federal counterparts. In contrast, federal-level agencies tend to enjoy larger network sizes, which they frequently leverage as a tool for disseminating information. Elected office holders, in general, managed large networks and leveraged their popularity during the crisis. This analysis offers insight for both scholars and practitioners in the areas of emergency management and public administration, as it helps to deepen our understanding of how government agencies and political leaders across various levels of government engage with the public during times of crisis.

2020  “Rise of the Machines? Examining the Influence of Social Bots on a Political Discussion Network” Social Science Computer Review

Using Twitter data on “Muller Investigation,” we investigated the roles of bots on political communication. We found that bots artificially boost the influentialness of the far-right community. We also found use of alternative media (including bots) for political communications.

 

2019  “Processes, Potential Benefits, and Limitations of Big Data Analytics: A Case Analysis of 311 Data from City of Miami,” The 20th Annual International Conference on Digital Government Research.

As part of the open government movement, an increasing number of 311 call centers have made their datasets available to the public. Studies have found that 311 request patterns are associated with personal attributes and living conditions. Most of these studies use New York City 311 data. In this study, we use 311 data from the City of Miami, a smaller local government, as a case study. This study contributes to digital government research and practices by making suggestions on best practices regarding the use of big data analytics on 311 data. In addition, we discuss limitations of 311 data and analytics results. Finally, we expect our results to inform decision making within the City of Miami government and other local governments.

2019  “Use of Multimedia Tweets in Health Communication: Analysis of Tweets on Zika Virus,” Information Research, 24(2)

Impact of multi-media use in Twitter communication in state emergency situations.

2018  “Crisis Communications in the Age of Social Media: A Network Analysis of Zika Related Tweets”, Social Science and Computer Review, 36(5), 523-541–This study is cited by the Wikipedia page on  “2015–16 Zika virus epidemic” below:

“Many studies have been conducted on the connections and impact of social media mentions of Zika. One analysis found that the primary topics discussed on Twitter before the peak of the outbreak regarding Zika included Zika’s impact, reactions to Zika, pregnancy and microcephaly, transmission routes of Zika, and case reports.[187]During the summer of 2016 when Zika was spreading at a much faster rate, this social media analysis determined that the major topics on Twitter regarding Zika had become concerns about the spread of Zika, criticism of Congress, news about Zika, and scientific information about Zika.[187] The same study also found that tweets from reputable institutions and people holding scientific credentials demonstrated the ability of Twitter as a source to spread information quickly on the internet.[187] ” 

tetweetpagerank

The R scripts to parse the Twitter stream JSON files and construct the retweet network are available at http://information-analytics.cas.usf.edu/zikastudy/contents.html

2018  “Government Social Media Communications during Zika Health Crisis”, in the Proceedings of the 19th Annual International Conference on Digital Government Research, May 30 – June 1, Delft, the Netherlands

This article examines the use of Twitter by federal, state, and local government actors during the 2015–2016 Zika virus outbreak in the United States. We learned that local governments have smaller network sizes. Federal level agencies
frequently use Twitter for information provision, using URLs and images while leveraging large network sizes. Elected office holders, in general, managed large networks, and leveraged their popularity during the crisis.