Miriam Boon | University of Regina (original) (raw)

Papers by Miriam Boon

23rd International Conference on Intelligent User Interfaces, 2018

News articles often use narrative frames to present people, organizations, and facts. These narra... more News articles often use narrative frames to present people, organizations, and facts. These narrative frames follow cultural archetypes, enabling readers to associate each of the presented elements with familiar stereotypes, well-known characters, and recognizable outcomes. In this way, authors can cast real people or organizations as heroes, villains, or victims. We present a system that identifies the main entities of a news article, and determines which is being cast as a hero, a villain, or a victim. As currently implemented, this system interacts directly with news consumers through a browser extension. Our hope is that by informing readers when an entity is cast in one of these roles, we can make implicit bias explicit, and thereby assist readers in applying their media literacy skills. This approach can also be used to identify roles in well-understood event sequences in a more prosaic manner, e.g., for information extraction.

Intelligent information technologies can be designed to automatically and immediately provide bot... more Intelligent information technologies can be designed to automatically and immediately provide both journalists and ordinary newsreaders with a broad range of the contextual information they need in order to understand news stories. Our work on specific systems has inspired the creation of a general architecture and platform for developing applications capable of automatically identifying, selecting, and presenting relevant contextual information. These systems can interact directly with news consumers through mechanisms such as browser extensions.

Media literacy allows individuals to better interpret the information they need to absorb to cont... more Media literacy allows individuals to better interpret the information they need to absorb to contribute to our democratic, knowledge-based society. I propose that by automatically notifying readers of an article's problematic pragmatic characteristics, an application could augment their media literacy. I describe two characteristics for which I have been building automatic classifiers -- factiness and tropes as narrative frames -- and discuss the status of each project.

Journal of Computer-Mediated Communication

Although artificial intelligence is blamed for many societal challenges, it also has underexplore... more Although artificial intelligence is blamed for many societal challenges, it also has underexplored potential in political contexts online. We rely on six preregistered experiments in three countries (N = 6,728) to test the expectation that AI and AI-assisted humans would be perceived more favorably than humans (a) across various content moderation, generation, and recommendation scenarios and (b) when exposing individuals to counter-attitudinal political information. Contrary to the preregistered hypotheses, participants see human agents as more just than AI across the scenarios tested, with the exception of news recommendations. At the same time, participants are not more open to counter-attitudinal information attributed to AI rather than a human or an AI-assisted human. These findings, which—with minor variations—emerged across countries, scenarios, and issues, suggest that human intervention is preferred online and that people reject dissimilar information regardless of its sour...

This preregistered project examines the general belief that news has a beneficial impact on socie... more This preregistered project examines the general belief that news has a beneficial impact on society. We test news exposure effects on desirable outcomes, i.e., political knowledge and participation, and detrimental outcomes, i.e., attitude and affective polarization, negative system perceptions, and worsened individual well-being. We rely on two complementary over-time experiments that combine participants' survey self-reports and their behavioral browsing data: one that incentivized participants taking a ‘news vacation’ for a week (N = 797; 30M visits) in the US, the other of 'news binging' for two weeks (N = 828; 17M visits) in Poland. Across both experiments, we demonstrate that reducing or increasing news exposure has little -- if any -- impact on the positive or negative outcomes tested. These robust null effects emerge irrespective of participants' prior levels of news consumption and whether prior news diet was like-minded, and regardless of compliance levels....

Proceedings of the 20th International Conference on Intelligent User Interfaces Companion - IUI Companion '15, 2015

Workshop on Language Technologies and Computational Social Science

Seeking information online can be an exercise in time wasted wading through repetitive, verbose t... more Seeking information online can be an exercise in time wasted wading through repetitive, verbose text with little actual content. Some documents are more densely populated with factoids than others. The densest documents are the most efficient use of time, likely to include the most information. This study explores this problem using crowdsourced ratings of the factual content of 772 online articles. The results suggest that after controlling for widely varying document length using Heaps’ Law, a significant positive correlation persists between perceived factual content and relative information entropy.

23rd International Conference on Intelligent User Interfaces, 2018

News articles often use narrative frames to present people, organizations, and facts. These narra... more News articles often use narrative frames to present people, organizations, and facts. These narrative frames follow cultural archetypes, enabling readers to associate each of the presented elements with familiar stereotypes, well-known characters, and recognizable outcomes. In this way, authors can cast real people or organizations as heroes, villains, or victims. We present a system that identifies the main entities of a news article, and determines which is being cast as a hero, a villain, or a victim. As currently implemented, this system interacts directly with news consumers through a browser extension. Our hope is that by informing readers when an entity is cast in one of these roles, we can make implicit bias explicit, and thereby assist readers in applying their media literacy skills. This approach can also be used to identify roles in well-understood event sequences in a more prosaic manner, e.g., for information extraction.

Intelligent information technologies can be designed to automatically and immediately provide bot... more Intelligent information technologies can be designed to automatically and immediately provide both journalists and ordinary newsreaders with a broad range of the contextual information they need in order to understand news stories. Our work on specific systems has inspired the creation of a general architecture and platform for developing applications capable of automatically identifying, selecting, and presenting relevant contextual information. These systems can interact directly with news consumers through mechanisms such as browser extensions.

Media literacy allows individuals to better interpret the information they need to absorb to cont... more Media literacy allows individuals to better interpret the information they need to absorb to contribute to our democratic, knowledge-based society. I propose that by automatically notifying readers of an article's problematic pragmatic characteristics, an application could augment their media literacy. I describe two characteristics for which I have been building automatic classifiers -- factiness and tropes as narrative frames -- and discuss the status of each project.

Journal of Computer-Mediated Communication

Although artificial intelligence is blamed for many societal challenges, it also has underexplore... more Although artificial intelligence is blamed for many societal challenges, it also has underexplored potential in political contexts online. We rely on six preregistered experiments in three countries (N = 6,728) to test the expectation that AI and AI-assisted humans would be perceived more favorably than humans (a) across various content moderation, generation, and recommendation scenarios and (b) when exposing individuals to counter-attitudinal political information. Contrary to the preregistered hypotheses, participants see human agents as more just than AI across the scenarios tested, with the exception of news recommendations. At the same time, participants are not more open to counter-attitudinal information attributed to AI rather than a human or an AI-assisted human. These findings, which—with minor variations—emerged across countries, scenarios, and issues, suggest that human intervention is preferred online and that people reject dissimilar information regardless of its sour...

This preregistered project examines the general belief that news has a beneficial impact on socie... more This preregistered project examines the general belief that news has a beneficial impact on society. We test news exposure effects on desirable outcomes, i.e., political knowledge and participation, and detrimental outcomes, i.e., attitude and affective polarization, negative system perceptions, and worsened individual well-being. We rely on two complementary over-time experiments that combine participants' survey self-reports and their behavioral browsing data: one that incentivized participants taking a ‘news vacation’ for a week (N = 797; 30M visits) in the US, the other of 'news binging' for two weeks (N = 828; 17M visits) in Poland. Across both experiments, we demonstrate that reducing or increasing news exposure has little -- if any -- impact on the positive or negative outcomes tested. These robust null effects emerge irrespective of participants' prior levels of news consumption and whether prior news diet was like-minded, and regardless of compliance levels....

Proceedings of the 20th International Conference on Intelligent User Interfaces Companion - IUI Companion '15, 2015

Workshop on Language Technologies and Computational Social Science

Seeking information online can be an exercise in time wasted wading through repetitive, verbose t... more Seeking information online can be an exercise in time wasted wading through repetitive, verbose text with little actual content. Some documents are more densely populated with factoids than others. The densest documents are the most efficient use of time, likely to include the most information. This study explores this problem using crowdsourced ratings of the factual content of 772 online articles. The results suggest that after controlling for widely varying document length using Heaps’ Law, a significant positive correlation persists between perceived factual content and relative information entropy.