I am a Ph.D. student at the College of Information Studies (iSchool) of the University of Maryland, College Park. My research interests include Data Mining, Machine Learning, NLP, Social Network Analysis, and Computational Journalism. To be more specific, I am much interested in developing computational solutions to ensure the quality of information surfacing on social media. Currently, I am working as a Research Assistant for my academic supervisor, Dr. Naeemul Hassan, who also leads the Computational Journalism Lab at the University of Maryland. I completed my MS in Engineering Science (Emphasis Computer Science) from the University of Mississippi (Ole Miss) and a BSc in Computer Science and Engineering from the Bangladesh University of Engineering and Technology (BUET).
| Mar 1, 2021 | Alhamdulillah! I will be joining Adobe this summer as an HCI research intern. |
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| Dec 23, 2020 | Alhamdulillah! Our paper titled "Exploring the Tensions between the Owners and the Drivers of Uber Cars in Urban Bangladesh" has been accepted in CSCW 2021. |
| Dec 12, 2020 | Alhamdulillah! Our paper titled "Does Clickbait Actually Attract More Clicks? Three Clickbait studies you must read" has been accepted in CHI 2021. |
| Aug 31, 2020 | Alhamdulillah! Our short paper titled "ClaimViz: Visual Analytics for Identifying and Verifying Factual Claims" has been accepted in the 2020 IEEE VIS. |
| May 19, 2020 | Alhamdulillah! Our paper titled "Varying amounts of information in health news headlines can affect user selection and interactivity" has been accepted in AEJMC 2020. |
| Sep 10, 2019 | Alhamdulillah! Our paper titled Examining the Role of Clickbait Headlines to Engage Readers with Reliable Health-related Information" has been accepted for presentation at the AAAI 2019 Fall Symposium on AI for Social Good. |
| Aug 8, 2019 | Alhamdulillah! Joined University of Maryland, College Park as a Graduate Teaching Assistant |
| Jul 30, 2019 | Left University of Mississippi |
| Jul 11, 2019 | Alhamdulillah! I have successfully defended my MS Thesis titled "Towards Misleading Connection Mining" |
| Jul 05, 2019 | Alhamdulillah! Our manuscript titled "Misleading Connection Mining: Scopes, Computational Challenges and Future Directions" has been accepted as a poster in SocInfo 2019 |
| May 14, 2019 | Attended MisinfoWorkshop 2019 at San Francisco and presented our work titled "Differences in Health News from Reliable and Unreliable Media" |
| Feb 25, 2019 | Alhamdulillah! Our paper titled "Differences in Health News from Reliable and Unreliable Media" has been accepted in the MisinfoWorkshop 2019 |
| Feb 1-2, 2019 | Presented our works at C+J Symposium, 2019, Miami, FL, US |
| Nov 29, 2018 | Alhamdulillah! Paper titled “A Large-scale Study of Social Media Sources in News Articles” has been accepted in C+J 2019 |
| Nov 29, 2018 | Alhamdulillah! Paper titled “Fact-checking Initiatives in Bangladesh, India, and Nepal: A Study of User Engagement and Challenges” has been accepted in C+J 2019 |
| Oct 31, 2018 | Paper titled “Fact-checking Initiatives in Bangladesh, India, and Nepal: A Study of User Engagement and Challenges” submitted in C+J 2019 |
| Oct 31, 2018 | Paper titled “Differences between Health Related News Articles from Reliable and Unreliable Media” submitted in C+J 2019 |
| Oct 31, 2018 | Paper titled “A Large-scale Study of Social Media Sources in News Articles” submitted in C+J 2019 |
| May 15, 2018 | Alhamdulillah! Paper titled “All the President’s tweets”: A Large-scale Study of Uses of Social Media Content in Online News” has been accepted in AEJMC 2018 |
| Jan 17, 2018 | Alhamdulillah! Our paper titled “Boon or Bane for Political Engagement: A Large-Scale Study of Normalization of Facebook” has been accepted in the 68th annual ICA conference, to be held in Prague, Czech Republic. |
| Jan 17, 2018 | Alhamdulillah! Our paper titled “Social Media as Source: A Large-scale Study of Mainstream and Unreliable News Sites” has been accepted in the AEJMC Midwinter Conference, 2018 |
| Nov 09, 2017 | Alhamdulillah! Our paper titled “BaitBuster: A Clickbait Identification Framework” submitted to AAAI 2018 demonstration track has been accepted |
| Nov 01, 2017 | Paper titled “Boon or Bane for Political Engagement: A Large-Scale Study of Normalization of Facebook” submitted to ICA 2018 |
| Sep 29, 2017 | Paper titled “BaitBuster: A Clickbait Identification Framework” has been submitted to AAAI 2018 Demonstration track |
| Sep 04, 2017 | Alhamdulillah! Our paper titled “BaitBuster: Destined to Save You Some Clicks” has been accepted in the 2017 Computation+Journalism symposium as a demo/poster. |
| Aug 1, 2017 | Paper titled “BaitBuster: Destined to Save You Some Clicks” submitted to Computation+Journalism symposium 2017. |
| Jun 1, 2017 | Paper titled “A Boon, Bane, or None for Political Engagement: Normalization of Facebook in 2016 U.S. Presidential Election Campaign” submitted to JMCQ 2017. |
| May 24, 2017 | Paper titled “NMAT: Interactive Tool for Analyzing News Media on Social Platforms” submitted in CIKM 2017. |
| May 15, 2017 | Alhamdulillah! Our paper titled “Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?” has been accepted in ASONAM 2017 as a full paper. |
| Mar 26, 2017 | Paper titled “Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?” submitted in ASONAM 2017. |
The term clickbait refers to a form of web content that employs writing formulas and linguistic techniques in headlines to trick readers into clicking links, but does not deliver on its promises. Although media scholars and pundits consistently show clickbait content in a bad light, the industry based on this type of content has been rapidly growing and reaching more and more people across the world. The growth of clickbait industry appears to have noticeable impact on the media ecosystem, as many traditional media organizations have started to use clickbait techniques to attract readers and generate revenue. The key purpose of this project is to systematically quantify the extents to which traditional print and broadcast media as well as the “unreliable” media use clickbait properties in contents published on the web.
Read Paper Presentation PosterBaitBuster is a clickbait solution framework which aims to improve the web surfing experience of general users. It consists of a browser extension that identifies clickbaits present in a Facebook timeline and a Facebook page which is administered by a bot through the Facebook API. It not only detects clickbaits floating on the web but also provides a brief explanation behind its action. The extension is publicly available for use.
Read Paper Presentation Poster Website Chrome ExtensionFake news and misinformation spread in developing countries as fast as they do in developed countries with increasing penetration of the internet and social media. However, fighting misinformation is more difficult in developing countries where resources and necessary technologies are scarce. The main purpose of this project is to identify the challenges various fact-checking initiatives face in three South Asian countries–Bangladesh, India, and Nepal and recommend a sustainable solution.
Read Paper PresentationMisinformation spreading is an issue that attracts the attention of many researchers. But health disinformation is a relatively unexplored area. Consequences of misleading or erroneous health news can be very critical. Believing health misinformation may lead to a hazardous health condition. The goal of this study is to identify the structural, topical, and semantic patterns which are different in contents from reliable and unreliable media outlets. We believe these patterns can be leveraged to build a machine learning based solution for combating the health disinformation problem.
Read Paper Presentation PosterMedia organizations use Social Networking Sites (SNSs) not only as a medium of news dissemination but also as a source of news collection. Journalists like to quote and paraphrase contents regularly from social media pages. This project aims to investigate social media sourcing pattern from different perspectives.
Read Paper PosterThis project investigated the influence of social media in the election campaign based on a theoretical framework named "Normalization of the Cyberspace". We examined engagement on two verified Facebook pages run by the campaigns of two main candidates of the 2016 U.S. presidential election—Donald Trump and Hillary Clinton. We combine two computational methods—sentiment analysis and automated topic classification—and a quantitative content analysis method to analyze user engagement data.
Read Paper PosterDetermining the veracity of a factual claim made by public figures, aka fact-checking, is a common task of the journalists in the newsrooms. One critical challenge that they face while fact-checking is- they have to swift through a large amount of text to find claims that are checkworthy. While there exist some computational methods for automating the fact-checking process, little research has been done on how a system should combine such techniques with visualizations to assist journalists. ClaimViz is a visual analytic system that integrates machine learning methods with interactive visualizations to facilitate the fact-checking process for journalists. The design of ClaimViz is based on analyzing the requirements of real fact-checkers and our case studies demonstrate how the system can help users to effectively spot and verify claims.
Mass media plays a central role in delivering science-based crisis, risk, and healthcare information to the general public. However, we have shown a gap between what scholars and expert practitioners advise based on scientific guidelines and what mass media communicates about risk and healthcare. This project test AI, NLP, and data visualization methods to see how well they can close the gap between best practices in communicating science-based knowledge and current mass media practices focusing primarily on news stories. Our approach can assist mass media content creators in preparing effective and high-quality health information that conforms to science-based criteria, and assist media consumers in finding the highest quality information.
| Md Main Uddin Rony, Enamul Hoque, Naeemul Hassan.ClaimViz: Visual Analytics for Identifying andVerifying Factual Claims. In Proceedings of the IEEE Information Visualization Conference, October, 2020. [Paper] [Presentation] [Demo] |
| Ron Yaros, Md Mahfuzul Haque, Md Main Uddin Rony, Naeemul Hassan.Varying amounts of information inhealth news headlines can affect user selection and interactivity. In Proceedings of the Association for Educationin Journalism and Mass Communication (AEJMC) conference, San Francisco, USA, August, 2020 [Paper] [Poster] |
| Sameer Dhoju, Md Main Uddin Rony, Muhammad Ashad Kabir, Naeemul Hassan. Differences in Health News from Reliable and Unreliable Media. In Companion Proceedings of The 2019 World Wide Web Conference, pp. 981-987. ACM, 2019. [Paper] [Poster] |
| Md Mahfuzul Haque, Mohammad Yousuf, Zahedur Arman, Md Main Uddin Rony, Ahmed Shatil Alam, Kazi Mehedi Hasan, Md Khadimul Islam, Naeemul Hassan. Fact-checking Initiatives in Bangladesh, India, and Nepal: A Study of User Engagement and Challenges. In Proceedings of the 2019 Computation+Journalism Symposium (C+J2019), Miami, USA, February, 2019. [Paper] |
| Md Main Uddin Rony, Mohammad Yousuf, Naeemul Hassan. A Large-scale Study of Social Media Sources in News Articles. In Proceedings of the 2019 Computation+Journalism Symposium (C+J2019), Miami, USA, February, 2019. [Paper] [Poster] |
| Mohammad Yousuf, Naeemul Hassan, Md Main Uddin Rony. Social Media as Source: A Large-scale Study of Mainstream and Unreliable News Sites. In Proceedings of the Association for Education in Journalism and Mass Communication (AEJMC) Midwinter conference, Oklahoma, USA, March, 2018. |
| Mohammad Yousuf, Naeemul Hassan, Md Main Uddin Rony. Boon or Bane for Political Engagement: A Large-Scale Study of Normalization of Facebook. In Proceedings of the 68th International Communication Association (ICA) annual conference, Prague, Czech Republic, May, 2018. [Paper] |
| Md Main Uddin Rony, Naeemul Hassan, Mohammad Yousuf. BaitBuster: A Clickbait Identification Framework. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), New orleans, Louisiana, USA, February, 2018. [Paper] [Poster] |
| Md Main Uddin Rony, Naeemul Hassan, Mohammad Yousuf. BaitBuster: Destined to Save You Some Clicks. In Proceedings of the 2017 Computation+Journalism Symposium (C+J2017), Illinois, October, 2017. [Paper] |
| Md Main Uddin Rony, Naeemul Hassan, Mohammad Yousuf. Diving Deep into Clickbaits: Who Use Them to What Extents in Which Topics with What Effects?. In Proceedings of 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2017), July, 2017. [Paper] [Poster] |
Currently, I am a Research Assistant at Computational Journalism Lab (CJLab). CJLab is a research facility in the Philip Merrill College of Journalism at the University of Maryland, College Park. The goal of this lab is to advance the field of computational journalism by exploring interdisciplinary problems at the intersection of computation, information science, and journalism and thereby address issues with big societal impact.
Currently, I am working as a Teaching Assistant for Dr. Amanda Lazar and Ed Summers.
I worked as a Research Assistant for Dr. Naeemul Hassan, a computer science professor at the University of Mississippi, on several projects since January 2017. Dr. Hassan directs Data Exploration and Research Laboratory (dear.lab). The goal of this lab is to advance database and data mining research and thereby address issues with big societal impact. The lab's current focus includes computational journalism, multidimensional optimization, and natural language processing.
My quest for Data Analytics began when I joined Infolytx as a Software Engineer. I was very lucky as I got the opportunity to learn from Dr. Zunaid Kazi, a former IBM researcher, directly. Infolytx is an AI and Machine Learning company building solutions to help healthcare and other high-tech industries understand and monetize their data.
A Java-based PaaS Solution where content from sources like FDA and social media has been parsed, analyzed using Big Data technology to build a Machine Learning Predictive Model for adverse drugs reaction intelligence.
Key Technologies Used:
A data-driven physician ranking and drug sales recommendation device built on analysis of large amount of 3rd party physician biographical data and prescription data.
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An Augmented Reality App for customers where the retailer is able to advertise specials using 3D imagery.
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Right after the completion of undergrad study, I joined Nascenia IT. Nascenia developed web and mobile-based application for its North American and European clients.
It is a comprehensive Transportation Management Software (TMS) solution designed to make life easier for medium to large transportation intermediaries dealing in TL and LTL freight.
Key Technologies Used:
Welltravel is a platform which enables travelers to find and book flights, hotels and rental cars for their trip..
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