25,697 research outputs found
Data Portraits and Intermediary Topics: Encouraging Exploration of Politically Diverse Profiles
In micro-blogging platforms, people connect and interact with others.
However, due to cognitive biases, they tend to interact with like-minded people
and read agreeable information only. Many efforts to make people connect with
those who think differently have not worked well. In this paper, we
hypothesize, first, that previous approaches have not worked because they have
been direct -- they have tried to explicitly connect people with those having
opposing views on sensitive issues. Second, that neither recommendation or
presentation of information by themselves are enough to encourage behavioral
change. We propose a platform that mixes a recommender algorithm and a
visualization-based user interface to explore recommendations. It recommends
politically diverse profiles in terms of distance of latent topics, and
displays those recommendations in a visual representation of each user's
personal content. We performed an "in the wild" evaluation of this platform,
and found that people explored more recommendations when using a biased
algorithm instead of ours. In line with our hypothesis, we also found that the
mixture of our recommender algorithm and our user interface, allowed
politically interested users to exhibit an unbiased exploration of the
recommended profiles. Finally, our results contribute insights in two aspects:
first, which individual differences are important when designing platforms
aimed at behavioral change; and second, which algorithms and user interfaces
should be mixed to help users avoid cognitive mechanisms that lead to biased
behavior.Comment: 12 pages, 7 figures. To be presented at ACM Intelligent User
Interfaces 201
QuizMap: Open social student modeling and adaptive navigation support with TreeMaps
In this paper, we present a novel approach to integrate social adaptive navigation support for self-assessment questions with an open student model using QuizMap, a TreeMap-based interface. By exposing student model in contrast to student peers and the whole class, QuizMap attempts to provide social guidance and increase student performance. The paper explains the nature of the QuizMap approach and its implementation in the context of self-assessment questions for Java programming. It also presents the design of a semester-long classroom study that we ran to evaluate QuizMap and reports the evaluation results. © 2011 Springer-Verlag Berlin Heidelberg
Detecting frames in news headlines and its application to analyzing news framing trends surrounding U.S. gun violence
Different news articles about the same topic often offer a variety of perspectives: an article written about gun violence might emphasize gun control, while another might promote 2nd Amendment rights, and yet a third might focus on mental health issues. In communication research, these different perspectives are known as âframesâ, which, when used in news media will influence the opinion of their readers in multiple ways. In this paper, we present a method for effectively detecting frames in news headlines. Our training and performance evaluation is based on a new dataset of news
headlines related to the issue of gun violence in the United States. This Gun Violence Frame
Corpus (GVFC) was curated and annotated by
journalism and communication experts. Our
proposed approach sets a new state-of-the-art
performance for multiclass news frame detection, significantly outperforming a recent baseline by 35.9% absolute difference in accuracy. We apply our frame detection approach in a large scale study of 88k news headlines about the coverage of gun violence in the U.S. between 2016 and 2018.Published versio
Analytic frameworks for assessing dialogic argumentation in online learning environments
Over the last decade, researchers have developed sophisticated online learning environments to support students engaging in argumentation. This review first considers the range of functionalities incorporated within these online environments. The review then presents five categories of analytic frameworks focusing on (1) formal argumentation structure, (2) normative quality, (3) nature and function of contributions within the dialog, (4) epistemic nature of reasoning, and (5) patterns and trajectories of participant interaction. Example analytic frameworks from each category are presented in detail rich enough to illustrate their nature and structure. This rich detail is intended to facilitate researchersâ identification of possible frameworks to draw upon in developing or adopting analytic methods for their own work. Each framework is applied to a shared segment of student dialog to facilitate this illustration and comparison process. Synthetic discussions of each category consider the frameworks in light of the underlying theoretical perspectives on argumentation, pedagogical goals, and online environmental structures. Ultimately the review underscores the diversity of perspectives represented in this research, the importance of clearly specifying theoretical and environmental commitments throughout the process of developing or adopting an analytic framework, and the role of analytic frameworks in the future development of online learning environments for argumentation
Code Park: A New 3D Code Visualization Tool
We introduce Code Park, a novel tool for visualizing codebases in a 3D
game-like environment. Code Park aims to improve a programmer's understanding
of an existing codebase in a manner that is both engaging and intuitive,
appealing to novice users such as students. It achieves these goals by laying
out the codebase in a 3D park-like environment. Each class in the codebase is
represented as a 3D room-like structure. Constituent parts of the class
(variable, member functions, etc.) are laid out on the walls, resembling a
syntax-aware "wallpaper". The users can interact with the codebase using an
overview, and a first-person viewer mode. We conducted two user studies to
evaluate Code Park's usability and suitability for organizing an existing
project. Our results indicate that Code Park is easy to get familiar with and
significantly helps in code understanding compared to a traditional IDE.
Further, the users unanimously believed that Code Park was a fun tool to work
with.Comment: Accepted for publication in 2017 IEEE Working Conference on Software
Visualization (VISSOFT 2017); Supplementary video:
https://www.youtube.com/watch?v=LUiy1M9hUK
LEARNING HOW STUDENTS ARE LEARNING IN PROGRAMMING LAB SESSIONS
Department of Computer Science and EngineeringProgramming lab sessions help students learn to program in a practical way. Although these sessions
are typically valuable to students, it is not uncommon for some participants to fall behind throughout
the sessions and leave without fully grasping the concepts covered during the session. In my thesis, I
will be presenting LabEX, a system for instructors to understand students' progress and learning
experience during programming lab sessions. LabEX utilizes statistical techniques that help
distinguishing struggling students and understand their degree of struggle. LabEX also helps instructors
to provide in-situ feedback to students with its real-time code review. LabEX was evaluated in an entry-level
programming course taken by more than two hundred students in UNIST, establishing that it
increases the quality of programming lab sessions.ope
Detecting and Monitoring Hate Speech in Twitter
Social Media are sensors in the real world that can be used to measure the pulse of societies.
However, the massive and unfiltered feed of messages posted in social media is a phenomenon that
nowadays raises social alarms, especially when these messages contain hate speech targeted to a
specific individual or group. In this context, governments and non-governmental organizations
(NGOs) are concerned about the possible negative impact that these messages can have on individuals
or on the society. In this paper, we present HaterNet, an intelligent system currently being used by
the Spanish National Office Against Hate Crimes of the Spanish State Secretariat for Security that
identifies and monitors the evolution of hate speech in Twitter. The contributions of this research
are many-fold: (1) It introduces the first intelligent system that monitors and visualizes, using social
network analysis techniques, hate speech in Social Media. (2) It introduces a novel public dataset on
hate speech in Spanish consisting of 6000 expert-labeled tweets. (3) It compares several classification
approaches based on different document representation strategies and text classification models. (4)
The best approach consists of a combination of a LTSM+MLP neural network that takes as input the
tweetâs word, emoji, and expression tokensâ embeddings enriched by the tf-idf, and obtains an area
under the curve (AUC) of 0.828 on our dataset, outperforming previous methods presented in the
literatureThe work by Quijano-Sanchez was supported by the Spanish Ministry of Science and Innovation
grant FJCI-2016-28855. The research of Liberatore was supported by the Government of Spain, grant MTM2015-65803-R, and by the European Unionâs Horizon 2020 Research and Innovation Programme, under the Marie Sklodowska-Curie grant agreement No. 691161 (GEOSAFE). All the financial support is gratefully acknowledge
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