This study proposes a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists’ emotions when visiting a city’s tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and activities like concerts, impact tourists’ emotions. In addition, our analysis suggests that tourists experience greater levels of enjoyment in places such as observatories rather than zoos. Finally, we find that local and international visitors tend to convey negative sentiment when visiting more than one attraction in a day whereas the opposite holds for out of state visitors. Below you will see some interesting results we gathered. Full text here.


Our following two papers have been presented at the Annual Simulation Symposium at Spring Simulation Multi-Conference 2018.

  • Big Data, Agents, and Machine Learning: towards A Data-Driven Agent-based Modeling Approach
  • Assessing the Impact of Cyberloafing on Cyber Risk

GMU Logo

Today is my first day at George Mason University (GMU) as a postdoc/research associate. I’ve joined a wonderful team of scholars from GMU and Tulane University to work on an agent-based simulation project funded by DARPA. Very excited for this new chapter in my life.


  • I am presenting my dissertation topic at the ODU’s 3MT (Three Minute Thesis) challenge. The event will be held at the University Theatre at ODU on October 24, 2017 5:00 – 8:00 p.m.
  • The 51th Annual Simulation Symposium (ANNS’18) full paper submission deadline is extended to December 14, 2017. Looking forward to receiving your submissions.
  • The Virtual City short article on sim4all.

I have attended the Swarmfest 2017 and presented an introductory tutorial to CLOUDES. Chris Lynch presented our paper titled “Identifying Unexpected Behaviors of Agent-based Models through Spatial Plots and Heat Maps”. It was a great conference with discussions and exchange of ideas, and Joshua M. Epstein as the keynote speaker.


I have presented two papers in the Spring Simulation Multi-Conference 2017 (Virginia Beach, VA, USA). The first paper is a cybersecurity simulation paper titled The Spread of Wi-Fi Router Malware Revisited. Presented within the 20th Communications and Networking Symposium, this paper investigated the spread of malware via Wi-Fi router vulnerabilities from a data-driven perspective. The second paper is titled “A Data-Driven Spatial Agent-Based Simulation Application With In-Memory Caching Support” and presented in the demo session.


Our new paper on teaching discrete-event simulation using games was presented by my colleague Chris Lynch at the 2016 Winter Simulation Conference. What makes this work cool is that it is co-authored by four high school students in Suffolk, VA.


Our enhanced trace validation of agent-based models paper was published in the Sage journal SIMULATION: Transactions of The Society for Modeling and Simulation International. Here is the abstract of this work:

The verification and validation (V&V) of agent-based models (ABMs) is challenging. The underlying structure of the model and the agents can change over time. Furthermore, the theoretical context of the model is often very different from established models of the same phenomenon. In an effort to overcome these issues, trace validation is becoming a common V&V mechanism within the agent-based modeling community. In trace validation, characteristics of agents and the model are tracked over time and then analyzed by subject matter experts (SMEs) to gain insight into unexpected and potentially invalid output. Here, we present our tool, the V&V Calculator, which applies predicates employed in the field of software engineering. The result is a structured trace validation approach with quantifiable measures that facilitates SME exploration and insight into the causes of unexpected output within ABMs.