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Qatar Computing Research Institute

Scientist

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Yelena Mejova is a scientist at the Qatar Computing Research Institute in the Social Computing Group. Her research concerns the use of Social Media in health informatics, especially in lifestyle diseases, as well as for tracking political speech and other cultural phenomena. As a post-doc at Yahoo Research Barcelona, she was a part of Web Mining and User Engagement groups, working with Mounia Lalmas on the Linguistically Motivated Semantic Aggregation Engines project.



Jul 20, 2017
Invited to speak at International Conference on Complex Networks CompleNet taking place in Boston, MA on March 5-8, 2018.
 
Mar 20, 2017
Presenting a Tutorial on Social Media for Health Research at ICWSM in May 15, 2017 with Ingmar Weber and Kenneth W. Goodman. Register before March 31 to get Early Bird rates.
 
Dec 4, 2016
Co-chairing the first stand-alone edition of Digital Health Conference, submit your papers by Feb 13, 2017!
 
Oct 2, 2016
Co-editing Digital Data for Nutrition, Healthy Eating and Exercise, a special journal issue of Frontiers. Submit your work by Nov 30!
 
Mar 20, 2016
Our work on #foodporn on Instagram has been featured on MIT Tech Review, N+1(ru), and Gizmodo. Explore the data on foodporn.qcri.org
 
Nov 24, 2015
Chairing PhD Track and Health Challenge at the Digital Health Conference. Students will get feedback on their dissertations and learn about gamification and social media analysis.
 
Oct 30, 2015
Organizing the Social Computing for Health track at Digital Health Conference (co-located with WWW in Montreal, Canada)
 
Jun 15, 2015
Our team won the Challenge22 prize for innovation and a chance to be incubated for a year in aims of creating a lasting legacy for Qatar and the region
 



   


#Halal on Social Media: Religion, Commerce, Health
Benkhedda Youcef (Ecole Nationale Supérieure d’Informatique, Algeria)
Khairani (University of Indonesia)

Frontiers in Digital Humanities: Big Data'17

Halal is a religious term, a cultural staple, and huge market. Here, we investigate the meaning of halal in three global communities speaking Arabic, Bahasa Indonesian, and English. All three have a unique perception of this concept, identifying it more with trade, food, or cosmetics. Showing a complicated relationship with both religious and governmental authority, the concept of halal has its own life on the social media, redefining its traditional and market space.
   


Tracking Health Misinformation on Twitter: case of Zika
Amira Ghenai (University of Waterloo)

ICHI'17

Misinformation and rumors in the health domain may not only cause inconvenience, but may increase medical care costs and even lead to the loss of life. Here, we build a pipeline for tracking Zika misinformation during the first half of 2016 when its incidence spiked in South America, incorporating crowdsourcing with machine learning.


Using Facebook Ads Audiences for Global Lifestyle Disease Surveillance
Ingmar Weber (QCRI)
Matheus Araújo (Federal University of Minas Gerais)
Fabricio Benevenuto (Federal University of Minas Gerais)

ICWSM'17 | WebSci'17 | Demo

In this series of studies we explore the use of demographically rich Facebook Ads audience estimates for tracking non-communicable diseases around the world, and especially in the Middle East. We compute the audiences of health "marker" interests, and evaluate their potential in tracking health conditions associated with lifestyle-related health conditions associated with tobacco use, obesity, and diabetes, as well as compare these to the performance of "placebo" interests.



    


Revisiting the American Voter
Huyen Le, Bob Boynton, Zubair Shafiq, Padmini Srinivasan (University of Iowa)

CHI'17 | HT'17

The American Voter – a seminal work in political science – uncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this work, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media.







Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web
Sina Sajadmanesh, Sina Jafarzadeh, Seyed Ali Ossia, Hamid R. Rabiee, Hamed Haddadi,
Yelena Mejova, Mirco Musolesi, Emiliano De Cristofaro, Gianluca Stringhini



A large-scale study of recipes published on the Web and their content. Using a database of more than 157K recipes from over 200 different cuisines, we analyze ingredients, flavors, and nutritional values which distinguish dishes from different regions, and use this knowledge to assess the predictability of recipes from different cuisines. We then use country health statistics to understand the relation between these factors and health indicators of different nations, such as obesity, diabetes, migration, and health expenditure.




Cultural Pluralism: case of Charlie Hebdo
Jisun An (QCRI)
Haewoon Kwak (QCRI)
Sonia Alonso Saenz De Oger (Georgetown University, Qatar)
Braulio Gomez Fortes (Deusto University)

ICWSM'16

We ask whether the stances on the issue of freedom of speech can be modeled using established sociological theories, including Huntington’s culturalist Clash of Civilizations, and those taking into consideration social context, including Density and Interdependence theories. At an individual level, we find social context to play a significant role, with non-Arabs living in Arab countries using #JeSuisAhmed (“I am Ahmed”) five times more often when they are embedded in a mixed Arab/non-Arab (mention) network.




Privacy and Twitter in Qatar: Traditional Values in the Digital World
Norah Abokhodair (University of Washington)
Sofiane Abbar (QCRI)
Sarah Vieweg (QCRI)

WebSci'16

We explore the meaning of "privacy" from the perspective of Qatari nationals as it manifests in digital environments. Our mixed-methods analysis of 18K Twitter posts that mention "privacy" focuses on the online and offline contexts in which privacy is mentioned, and how those contexts lead to varied ideologies regarding privacy.





Crowdsourcing Health Labels
Ingmar Weber (QCRI)

Digital Health'16

Is it feasible to use profile pictures to infer a user's health, such as weight? We show that this is indeed possible and further show that the fraction of labeled-as-overweight users is higher in U.S. counties with higher obesity rates. As obesity-related conditions such as diabetes, heart disease, osteoarthritis, and even cancer are on the rise, this obese-or-not label could be one of the most useful for studies in public health.



#Foodporn and Health Around the World
Sofiane Abbar (QCRI)
Hamed Haddadi (Queen Mary University of London)


How is food redefined in social media? Does food fetishizing via a plethora of images shifting our understanding of food? Our international study of #foodporn hashtag on Instagram shows the obsession with chocolate and sweets, but also reveals a tendency of the communities to like and comment more on healthier content, suggesting a new avenue for healthy lifestyle interventions.



Health in Qatar
Hamed Haddadi (Queen Mary University of London)
Ingmar Weber (QCRI)
Sofiane Abbar (QCRI)
Azadeh Ghahghaei (Freie Universitat Berlin)


Using a near-complete dataset of Instagram checkins in Qatar, we examine the behavior of Arabic- and English-speaking populations. We find behavior changes around major religious holidays, including Ramadan, which affects the dietary patterns of this highly diverse country.


View on Obesity through Instagram
Ingmar Weber (QCRI)
Hamed Haddadi (Queen Mary University of London)
Anastasios Noulas (University of Cambridge)


Using millions of Instagram posts in locations all over US, we examine the social media signals surrounding obesity. Our analysis reveals a relationship between small businesses and local foods with better dietary health, yet a tendency of social media users to reinforce unhealthy dietary habits through likes and comments, with donuts and cupcakes being the most "liked" foods.



Twitter: A Digital Socioscope
Ingmar Weber (QCRI)
Michael Macy (Cornell)


This book surveys how to use Twitter data to study human behavior and social interaction on a global scale. It is a reference for behavioral and social scientists who want to explore the use of online data in their research, and for non-professionals that follow the social impact of new technologies.



Relating Social Media Users to Little-known Content
Ingmar Weber (QCRI)
Javier Borge-Holthoefer (QCRI)


Long-tail content -- news stories, music, even people -- may need a little more help in order for people to notice them. We combine the notions of serendipity and explainability to build "bridges" between content and users, utilizing high-quality knowledge bases as well as users' interests profiles, as estimated using their social media presence.




Controversy and Sentiment in News
Carlos Castillo (QCRI)
Nicholas Diakopoulos (University of Maryland)
Amy X. Zhang (MIT CSAIL)

In the news: CrowdFlower  Source

Using lexical resources, such as those on sentiment and bias, we explore the use of emotional language around controversial topics by mainstream news agencies. Our aim is to eventually detect these controversial topics and to automatically find the sides of the discussion.



Monitoring Dietary Health via Social Media
Ingmar Weber (QCRI)
Sofiane Abbar (QCRI)
Hamed Haddadi (QCRI)


Using online check-ins and posts related to food, we track diet-related diseases like obesity and diabetes, and relate the perceptions of food to the demographics of the individuals. Social media also gives us an opportunity to explore the relationship between social connections and dietary habits -- indeed, there seem to be a connection between your social-media-detected diet and that of your friends.



Linguistically Motivated Semantic Aggregation Engines (LiMoSINe)
Ilaria Bordino (Yahoo Labs Barcelona)
Mounia Lalmas (Yahoo London)
Olivier Van Laere (Yahoo Labs Barcelona)
Byungkyu Kang (UC Santa Barbara)



As a part of the LiMoSINe EU project, we are building search engines based on semantics found in large document collections. These semantics include entities, sentiment expressed about them, the quality of writing about them, their topical categorization, and, of course, the relationships between these entities. Our faceted search prototype allows the user to explore the web of entities, adjusting the data views along various metadata attributes.



Understanding Donation Behavior through Email
Ingmar Weber (Qatar Computing Research Institute)
Venkata Rama Kiran Garimella (Aalto University)
Michael C Dougal (UC Berkeley)


We analyze a two-month anonymized email log from several perspectives motivated by past studies on charitable giving: (i) demographics, (ii) user interest, (iii) external time-related factors and (iv) social network influence. We show that email captures the demographic peculiarities of different interest groups, for instance, predicting demographic distributions found in the US 2012 Presidential Election exit polls. We show the importance of the social connection in predicting whether an individual donates, showing that, although annoying to the most of us, email campaigns can be effective.



Economic, Social, and Cultural Boundaries in International Communication
Ruth Garcia (Universitat Pompeu Fabra Barcelona)
Daniele Quercia (Yahoo Labs Barcelona)


In this study we show that the international Twitter communication landscape is not only still largely predetermined by physical distance, but that it also depends on countries' social, economic, and cultural attributes. This communication, as measured using @mentions, is correlated (r = 0.68) with the Gravity Model, which hypothesizes that the flow between two areas is proportional to their masses and inversely proportional to the distance between them. Our final model, which takes into consideration income, trade share, migration, language, and Hofstede's cultural variables, achieves an Adjusted R2 of 0.80.



Political Sentiment Classification & Tracking
Padmini Srinivasan (Computer Science, University of Iowa)
Bob Boynton (Political Science, University of Iowa)


Understanding the nature of political discourse on social media allows us to gauge the motivations of its constituent voices and representativeness of its message. A thorough evaluation of sentiment classification algorithms applied to political writings shows this to be a non-trivial task. 


Content Reuse in an Organization
Klaar De Schepper (Columbia University)
Lawrence Bergman (IBM T.J. Watson Research Center)
Jie Lu (IBM T.J. Watson Research Center)

CHI'11 [Honorable Mention]

How important is it for an organization to keep track of the content it generates? Turns out very much so. We track content reuse across a collection of slideshow presentations, modeling the flow of information within the organization. Our ethnographic survey and interviewing effort resulted in a set of guidelines for a content management system that supports modular content search, team management, and provenance tracking. 


Event Tracking in Social Media
Viet Ha-Thuc (University of Iowa)
Padmini Srinivasan (University of Iowa)


Large-scale analysis of social media such as blogs allows us a glimpse into the mind of a large segment of Earth's population. This record of people's thoughts can be leveraged to track significant events and discussion about them. Using Viet Ha-Thuc's new topic modeling approach we were able to track major news events over a period of time.