Data Engineering and Science

Researchers to Study Connection Between Online Misinformation and Real-World Violence

admin — Tue, 07 Feb 2023 18:12:32 +0000

Researchers to Study Connection Between Online Misinformation and Real-World Violence admin Tue, 02/07/2023 - 13:12

It is well known that predators lurk on the internet seeking to harm others through misinformation, bullying, and hate speech. What is not understood, however, is how online abuse and harassment like this spread via misinformation can lead to real, physical violence in communities.

To understand and counter this phenomenon, faculty with Georgia Tech’s College of Computing is leading a two-year study on the impact of online violence-provoking misinformation and hate speech toward minority populations.

Realizing the implication on public health and safety, the Center of Disease Control and Prevention (CDC) is funding the study through a $678,000 grant. Georgia Tech’s Srijan Kumar is the principal investigator of the CDC grant while Munmun De Choudhury is co-PI.

“The conversations we have and the information we consume on the web really shape our behavior not just online, but in the real-world,” said Kumar, an assistant professor with the School of Computational Science and Engineering. “We need systematic evaluations and an all-hands-on-deck approach to study what sort of societal impact harmful online content has on health, equity, integrity, and safety.”

Inspiration for this study comes from the researchers’ observations of prevalent hate speech and calls for racially motivated violence on the internet and social media. This issue became more prominent during the Covid-19 pandemic.

In their grant proposal, the researchers say more than 11,000 incidents of physical violence and online aggression against Asians were reported during the pandemic. They also state that misinformation about Covid-19 led to destruction of property and over 800 deaths.

To understand the connection between virtual misinformation and physical violence, the study has four stated goals:

Identify health misinformation that promotes community violence
Map and measure prevalence of violence-provoking health misinformation across social media platforms
Establish the causal impact of such misinformation on consumers’ reactions and intention to engage in harm
Design mitigation and intervention strategies to reduce the prevalence of such misinformation

According to the group, social media is often “ground-zero” for health misinformation where it spreads at exceptional speed and scale. That is why the team intends to study hate speech and misinformation on social media platforms Twitter and Reddit.

“The very use of these platforms is impacting us in different ways. Sometimes these impacts are good, sometimes they are bad,” said De Choudhury, an associate professor with the School of Interactive Computing. “As we think about our wellbeing and the role of these online platforms, we cannot ignore the very fact that misinformation on those platforms is affecting our wellbeing in negative ways.”

The group selected Twitter and Reddit specifically due to their prominence in networking and wide range of demographically diverse users, a fact supported by Pew Internet Research statistics.

Diversity of the two social media platforms make them the ideal ecosystem for what the group intends to observe: anti-Asian and Anti-Black violence-provoking misinformation.

Given the correlation of Covid-19 misinformation spread and increase of discrimination and violence toward Asian and Black communities during the pandemic, the researchers believe their findings will make meaningful impact for people affected by this public health issue.

For example, the group points out that misinformation masquerading as medical racism further targeted Black communities. As a result, this both degraded trust in institutions and diminished vaccine efficacy during the Covid-19 pandemic.

Purdue University Assistant Professor Laura Schwab-Reese, an expert in community and behavioral health, joins Kumar and De Choudhury the research group. Together, they will collaborate with the non-profit Anti-Defamation League during the study. Backed with CDC funding, the team will develop tools to study and find solutions to violence-provoking health misinformation.

For example, the researchers will start by developing algorithms to detect health misinformation and violence-provoking hate speech targeting minorities. These algorithms will rely on the latest machine learning methodologies and social media data sets.

From there, the group can build an interactive dashboard that maps the spread of violence-provoking misinformation online and offers analytic capabilities on the visualized data for end users. This will provide quantitative insight about the causal relationship between misinformation exposure and violent attitudes toward targeted communities.

Finally, the team will provide an intervention design plan to mitigate the impact of the misinformation. This will include presenting exploratory evaluation of interventions, and even creating new social media-based intervention tools that can interrupt misinformation.

By leveraging computing methods and interdisciplinary collaboration, the group is poised to make online and physical communities safer places for all.

“The reason we are partnering with the Anti-Defamation League and public health researchers is because community engagement is paramount in this work,” De Choudhury said. “One of the unique things about this study is that the computational techniques and interventions we will develop will be informed by the communities who are targeted by these incidents.”

Summary sentence

Srijan Kumar and Munmun De Choudhury receive CDC grant

Dateline

Wed, 10/12/2022 - 12:00

Contact

Bryant Wine, Communications Officer
bryant.wine@cc.gatech.edu

Location

Atlanta, GA

Associated importer

Keywords

Computational Science and Engineering

Core research areas

Cybersecurity

Data Engineering and Science

People and Technology

Public Service, Leadership, and Policy

Mercury ID

662017

Source updated

Wed, 10/12/2022 - 09:47

Georgia Tech Plans Tokyo Redesign Using Social Data – Including Tweets

bwaye3 — Tue, 19 Apr 2022 16:42:57 +0000

Georgia Tech Plans Tokyo Redesign Using Social Data – Including Tweets bwaye3 Tue, 04/19/2022 - 12:42

What if everyone in a neighborhood had a voice in redesigning it? How can city planners democratize future smart cities, big data analytics and decision-making by involving citizen participation?

That’s the vision of the Tokyo Smart City Studio, using GPS and other location data to track trends in human behavior. The studio is part of the Eco Urban Lab, directed by Perry Yang. In the Studio, Georgia Tech designers are changing the way we plan cities.

According to Yang, designers need to know, “how urban form accommodates flows of all kinds, including information, energy, and human movements, and how patterns of flows are mapped through physical configurations that change over time.” Using advanced analytics on a massive pool of data, designers can see how people choose to use a space. Then, they can make decisions based on real behavior rather than theoretical models or small surveys, Yang said.

Projects from the Studio recently drew Esri’s attention for their advanced use of geographic analytics. As part of the studio, students used large-scale location data to model traffic flows in different segments of Tokyo.

Esri is best known as the company that developed GIS (geographic information system) software which is widely used by city and regional planners. Esri's blog covers innovative use of geospatial data.

To date, the Studio has delivered smart-city proposals for three different Tokyo neighborhoods: Urawa-Misono in 2017, Kyojima in 2018-2019, and Shinagawa in 2020. Yang said this year’s project will involve the Nihonbashi district, home of the Tokyo Stock Exchange and a historic origin of Tokyo’s modern urban culture.

Tokyo is one of the busiest, most populous cities in the world, and as such, it’s difficult to create sustainable, healthy environments, said Yang. His studio focuses on global collaboration to solve the problems facing cities like Tokyo.

For the Nihonbashi district, the Studio is collaborating with the Department of Urban Engineering at the University of Tokyo; the Global Carbon Project; the National Institute for Environmental Studies, Japan; and the Mitsui Fudosan University of Tokyo Laboratory.

Thanks to the diversity of ideas that this collaboration generates, the Tokyo Smart City Studio proposals aren’t purely theoretical. Students work on real neighborhood needs identified by the local government, using real on-site data gathered and processed by groundbreaking methods. Massive amounts of data require AI techniques and algorithms to process some of them.

Design Makes Cities Smart

Unlike a smartphone or a smart home, a smart city is measured by more than its Internet connection or its automation. A city is smart because its design is based on data about flows of people, resources, energy, and information. “Empowered by new tools and technologies, cities are now far more designable than ever before. Future urban design and development are to be data-driven," Yang said.

"Cities are becoming more interactive and situation-driven and have to be more responsive, adaptable, and resilient to future conditions.”

Only in the past few years have smartphones, GPS, and Internet-of-Things (IoT) devices made real data on a city-wide scale available. These new technologies may enable good planning that is driven by social, institutional, and physical contexts, Yang said.

Students Predict Mobility Using AI Techniques

But new data and a new design philosophy require new methods of design, which haven’t been created yet. To meet this challenge, Yang’s students use AI techniques to create models of behavior.

An early test in Urawa-Misono used Tokyo traffic data. The model was “trained” using existing traffic data. Designers then check the model to see if correctly predicts congestion points. If it works, that suggests the model can be used to estimate the impact of design changes on traffic flow.

Methods like this allow designers to move mobility analytics into the design phase. Mobility is key in the urban environment, but mobility studies usually aren’t done until we envision how future urban spaces are shaped through design.

“Mobility research during these studios developed test processes to better integrate mobility metrics with design decisions,” Yang said.

The following studio in Kyojima expanded the role of deep learning techniques. Georgia Tech students participated in street experiments in Tokyo by carrying vital sensors to measure data such as heart beat, temperature, humidity, UV, pressure and acceleration of human movement, to understand human perception and their connections to urban street environments. Students created a rapid automatic assessment of sequential urban experiences: basically, how pleasant a person would experience walking down a street.

The resulting article, Computing Sequential Experience of an Urban Street using Deep Learning Technique, led by Helen Chen, a Ph.D. student in the School of City and Regional Planning, was presented at the 2019 International Conference of Urban Informatics.

Both the Urawa-Misono and Kyojima studio projects made mobility analysis and feedback part of the design phase, yielding designs better supporting resilience, sustainability, and community health.

Using Social Media to Check Risk of Heat Stress

In Tokyo, studio planners expanded mobility studies to include public health. Tokyo officials were concerned that heat waves would pose a risk to the 2020 Olympic crowds.

To address this, researchers used a combination of GPS and social networking service information to track people’s motion and response to heat “in near real-time [and] in high spatial resolution,” said Yang.

Students used thermal images from a helicopter to find hot zones. GPS data showed pedestrian exposure to those hot zones. The combination of heat and pedestrian exposure allowed prediction of risky areas.

In collaboration with partners in Japan, researchers searched geotagged twitter data for terms related to heat discomfort. They found a high correlation between the predicted risk zones and areas where people complained about heat.

Both the prediction of heat risk and the use of social media to check the prediction are new methods developed in the Studio.

Summary sentence

Students use big data and machine learning for neighborhood proposals.

Summary

Students in the Tokyo Smart City studio, of the Eco Urban Lab, are changing the way we plan cities. Using machine learning techniques on data from smartphones, GPS, and Internet-of-Things (IoT) devices, students develop proposals based on measured human experience.

Dateline

Tue, 04/05/2022 - 12:00

ann.hoevel@design.gatech.edu

Location

Atlanta, GA

Associated importer

Keywords

tokyo

Tokyo Smart City studio

Perry Pei-Ju Yang

eco urban lab

machine learning

gis

social media

big data analytics

Internet of Things

go-researchnews

News room topics

Society and Culture

Core research areas

Data Engineering and Science

People and Technology

Public Service, Leadership, and Policy

Mercury ID

657025

Source updated

Thu, 04/07/2022 - 15:05

Data Engineering and Science

Researchers to Study Connection Between Online Misinformation and Real-World Violence

Keywords

Categories

Core research areas

Georgia Tech Plans Tokyo Redesign Using Social Data – Including Tweets

Design Makes Cities Smart

Students Predict Mobility Using AI Techniques

Using Social Media to Check Risk of Heat Stress

Keywords

News room topics

Categories

Core research areas