Project Safe Neighborhood

Project Safe Neighborhood: Westwood Partnership to Prevent Juvenile Repeat Offenders is an interdisciplinary project involving the Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) – Wright State University with other community partners including the City of Dayton (Dayton Police Department), Montgomery County Juvenile Justice and University of Dayton to prevent juvenile repeat offenders from committing crime in the Westwood neighborhood located in the City of Dayton, Ohio.

People

Principal Investigators: Amit P. Sheth
Co-Investigators: Jack L. Dustin, Derek Doran
Graduate Students: Sanjaya Wijeratne, Lakshika Balasuriya,
Past Students: Pranav Karan

Overview

The U.S. 2010 Census reported the population living in Westwood (or the zip code 45417) as 31,281. According to Dayton Police Department's MIS records, one third of the felony arrests made in the first quarter of 2014 were juvenile repeat offenders from Westwood. As of April 2014, 120 of the 908 juveniles on probation in Montgomery County (population of 534,325 in 2012) have legal residence in Westwood. Furthermore, 50% of Montgomery County youth incarcerated at the Ohio Department of Youth Services reside in the Westwood neighborhood. Records from 2013 show that 249 juveniles from the Westwood neighborhood between the ages of 12-14, committed Aggravated Arson, Aggravated Robbery and Felonious Assault. These statistics caused Montgomery County Juvenile Justice and Dayton Police Department to partner with Wright State University and University of Dayton to seek a US Department of Justice grant to develop programs that reduce juvenile crime and repeat offenders. This initiative is titled: Project Safe Neighborhood - Westwood Partnership to Prevent Juvenile Repeat Offenders. The goals of the project includes:

1. Research and develop the criteria for identifying the most at risk youth
2. Establish the best practices for bringing all resources to common focus for these youth
3. Provided evidence-based strategies to address the pattern of crime in Westwood neighborhood and measure effectiveness of those strategies by a number of methods, including the use of social media.
4. Increase the use of law enforcement home visits in the targeted neighborhood
5. Enhance both the services and the sanctions made available through juvenile justice system

Related Work

• Wijeratne, S.; Doran, D.; Sheth, A.; Dustin, J.L., 'Analyzing the Social Media Footprint of Street Gangs,' in Intelligence and Security Informatics (ISI), 2015 IEEE International Conference on , vol., no., pp.91-96, 27-29 May 2015 doi: 10.1109/ISI.2015.7165945.

• Lakshika Balasuriya; Sanjaya Wijeratne; Derek Doran; Amit Sheth, 'Finding Street Gang Members on Twitter,' In The 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016) San Francisco, CA, USA; 2016.

• Sanjaya Wijeratne; Lakshika Balasuriya; Derek Doran; Amit Sheth, 'Word Embeddings to Enhance Twitter Gang Member Profile Identification,' In IJCAI Workshop on Semantic Machine Learning (SML 2016) New York City, NY: CEUR-WS; 2016.

• Sanjaya Wijeratne; 'Finding Street Gang Members on Twitter', Invited Talk at the Big Data Surveillance Analytics Mini Conference at Wright State University, Dayton, OH, USA. July, 2016.

• Lakshika Balasuriya; Sanjaya Wijeratne; Derek Doran; Amit Sheth, Signals Revealing Street Gang Members on Twitter, Talk given at the Workshop on Computational Approaches to Social Modeling (ChASM 2016) co-located with the 8th International Conference on Social Informatics (SocInfo 2016) Bellevue, WA, USA, 2016.

• Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran, EmojiNet: Building a Machine Readable Sense Inventory for Emoji, In 8th International Conference on Social Informatics (SocInfo 2016) Bellevue, WA, USA, 2016.

• Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran, EmojiNet: A Machine Readable Emoji Sense Inventory, Wright Brother's Day, Wright State University. Dayton, Ohio, USA, 2016.

Related Projects

Concurrent Projects

• kHealth: Semantic Multisensory Mobile Approach to Personalized Asthma Care
• Innovative NIDA National Early Warning Sysetm Network (iN3)
• Context-Aware Harassment Detection on Social Media
• Hazards SEES: Social and Physical Sensing Enabled Decision Support
• Market Driven Innovations and Scaling up of Twitris
• eDrugTrends: Social Media Analysis to Monitor Cannabis and Synthetic Cannabinoid Use
• Modeling Social Behavior for Healthcare Utilization in Depression
• MIDAS

Prior Projects

• PREDOSE: PREscription Drug abuse Online Surveillance and Epidemiology
• SoCS: Social Media Enhanced Organizational Sensemaking in Emergency Response

Funding

This project is sponsored by the Ohio Criminal Justice Services (OCJS) through the United States Attorney’s Office for the Southern District of Ohio for the Violent Gang and Gun Crime Reduction Program: Project Safe Neighborhood (2014-PS-PSN-431) under Grant No. 2014-PS- PSN-00006, titled: Westwood Partnership to Prevent Juvenile Repeat Offenders. Any opinions, findings, conclusions or recommendations expressed in this material are those of the investigator(s) and do not necessarily reflect the views of the sponsors.

Project Safe Neighborhood

Contact: Sanjaya Wijeratne