Search (8 results, page 1 of 1)

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Abstract

In 2021, sharing content is easier than ever. Our lingua franca is visual: memes, infographics, TikToks. Our references cross borders and platforms, shared and remixed a hundred different ways in minutes. Digital culture is collective by default and has us together all around the world. But as the internet reaches its "dirty 30s," what happens when pieces of digital culture that have been saved, screenshotted, and reposted for years need to retire? Let's dig into the story of one of these artifacts: The Lenna image. The Lenna image may be relatively unknown in pop culture today, but in the engineering world, it remains an icon. I first encountered the image in an undergrad class, then grad school, and then all over the sites and software I use every day as a tech worker like Github, OpenCV, Stack Overflow, and Quora. To understand where the image is today, you have to understand how it got here. So, I decided to scrape Google scholar, search, and reverse image search results to track down thousands of instances of the image across the internet (see more in the methods section).
Lena Forsén, the real human behind the Lenna image, was first published in Playboy in 1972. Soon after, USC engineers searching for a suitable test image for their image processing research sought inspiration from the magazine. They deemed Lenna the right fit and scanned the image into digital, RGB existence. From here, the story of the image follows the story of the internet. Lenna was one of the first inhabitants of ARPANet, the internet's predecessor, and then the world wide web. While the image's reach was limited to a few research papers in the '70s and '80s, in 1991, Lenna was featured on the cover of an engineering journal alongside another popular test image, Peppers. This caught the attention of Playboy, which threatened a copyright infringement lawsuit. Engineers who had grown attached to Lenna fought back. Ultimately, they prevailed, and as a Playboy VP reflected on the drama: "We decided we should exploit this because it is a phenomenon." The Playboy controversy canonized Lenna in engineering folklore and prompted an explosion of conversation about the image. Image hits on the internet rose to a peak number in 1995.
But despite this progress, almost 2 years later, the use of Lenna continues. The image appears on the internet in 30+ different languages in the last decade, including 10+ languages in 2021. The image's spread across digital geographies has mirrored this geographical growth, moving from mostly .org domains before 1990 to over 100 different domains today, notably .com and .edu, along with others. Within the .edu world, the Lenna image continues to appear in homework questions, class slides and to be hosted on educational and research sites, ensuring that it is passed down to new generations of engineers. Whether it's due to institutional negligence or defiance, it seems that for now, the image is here to stay.

Content

"Having known Lenna for almost a decade, I have struggled to understand what the story of the image means for what tech culture is and what it is becoming. To me, the crux of the Lenna story is how little power we have over our data and how it is used and abused. This threat seems disproportionately higher for women who are often overrepresented in internet content, but underrepresented in internet company leadership and decision making. Given this reality, engineering and product decisions will continue to consciously (and unconsciously) exclude our needs and concerns. While social norms are changing towards non-consensual data collection and data exploitation, digital norms seem to be moving in the opposite direction. Advancements in machine learning algorithms and data storage capabilities are only making data misuse easier. Whether the outcome is revenge porn or targeted ads, surveillance or discriminatory AI, if we want a world where our data can retire when it's outlived its time, or when it's directly harming our lives, we must create the tools and policies that empower data subjects to have a say in what happens to their data. including allowing their data to die."

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Abstract

Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture "crowd wisdom" and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user-generated stock predictions, based upon which they can make better investment decisions.

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Abstract

In using the Internet to solve everyday problems, older adults tend to find fewer correct answers compared to younger adults. Some authors have argued that these differences could be explained by age-related decline. The present study aimed to analyze the relationship between web-searching navigation and users' age, considering the Intelligence Quotient (IQ) and frequency of Internet and personal computer use. The intent was to identify differences due to age and not to other variables (that is, cognitive decline, expertise with the tool). Eighteen students (18-30?years) and 18 older adults (60-75?years) took part in the experiment. Inclusion criteria were the frequent use of computers and a web-searching activity; the older adults performed the Mini-Mental State Examination to exclude cognitive impairment. Participants were requested to perform the Kaufman Brief Intelligence Test 2nd ed. to measure their IQ level, and nine everyday web-searching tasks of differing complexity. The results showed that older participants spent more time on solving tasks than younger participants, but with the same accuracy as young people. Furthermore, nonverbal IQ improved performance in terms of time among the older participants. Age did not influence web-searching behavior in users with normal expertise and intelligence.

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Abstract

The rapid and wide dissemination of up-to-date, localized information is a central issue during disasters. Being attributed to the original 140-character length, Twitter provides its users with quick-posting and easy-forwarding features that facilitate the timely dissemination of warnings and alerts. However, a concern arises with respect to the terseness of tweets that restricts the amount of information conveyed in a tweet and thus increases a tweet's uncertainty. We tackle such concerns by proposing entropy as a measure for a tweet's uncertainty. Based on the perspectives of Uncertainty Reduction Theory (URT), we theorize that the more uncertain information of a disaster tweet, the higher the entropy, which will lead to a lower retweet count. By leveraging the statistical and predictive analyses, we provide evidence supporting that entropy validly and reliably assesses the uncertainty of a tweet. This study contributes to improving our understanding of information propagation on Twitter during disasters. Academically, we offer a new variable of entropy to measure a tweet's uncertainty, an important factor influencing disaster tweets' retweeting. Entropy plays a critical role to better comprehend URLs and emoticons as a means to convey information. Practically, this research suggests a set of guidelines for effectively crafting disaster messages on Twitter.

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Abstract

Web search is commonly used by fact checking systems as a source of evidence for claim verification. In this work, we demonstrate that the task of retrieving pages useful for fact checking, called evidential pages, is indeed different from the task of retrieving topically relevant pages that are typically optimized by search engines; thus, it should be handled differently. We conduct a comprehensive study on the performance of retrieving evidential pages over a test collection we developed for the task of re-ranking Web pages by usefulness for fact-checking. Results show that pages (retrieved by a commercial search engine) that are topically relevant to a claim are not always useful for verifying it, and that the engine's performance in retrieving evidential pages is weakly correlated with retrieval of topically relevant pages. Additionally, we identify types of evidence in evidential pages and some linguistic cues that can help predict page usefulness. Moreover, preliminary experiments show that a retrieval model leveraging those cues has a higher performance compared to the search engine. Finally, we show that existing systems have a long way to go to support effective fact checking. To that end, our work provides insights to guide design of better future systems for the task.

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Abstract

Social media connected the world--and gave rise to fake news and increasing polarization. Now a leading researcher at MIT draws on 20 years of research to show how these trends threaten our political, economic, and emotional health in this eye-opening exploration of the dark side of technological progress. Today we have the ability, unprecedented in human history, to amplify our interactions with each other through social media. It is paramount, MIT social media expert Sinan Aral says, that we recognize the outsized impact social media has on our culture, our democracy, and our lives in order to steer today's social technology toward good, while avoiding the ways it can pull us apart. Otherwise, we could fall victim to what Aral calls "The Hype Machine." As a senior researcher of the longest-running study of fake news ever conducted, Aral found that lies spread online farther and faster than the truth--a harrowing conclusion that was featured on the cover of Science magazine. Among the questions Aral explores following twenty years of field research: Did Russian interference change the 2016 election? And how is it affecting the vote in 2020? Why does fake news travel faster than the truth online? How do social ratings and automated sharing determine which products succeed and fail? How does social media affect our kids? First, Aral links alarming data and statistics to three accelerating social media shifts: hyper-socialization, personalized mass persuasion, and the tyranny of trends. Next, he grapples with the consequences of the Hype Machine for elections, businesses, dating, and health. Finally, he maps out strategies for navigating the Hype Machine, offering his singular guidance for managing social media to fulfill its promise going forward. Rarely has a book so directly wrestled with the secret forces that drive the news cycle every day"

Content

Inhalt: Pandemics, Promise, and Peril -- The New Social Age -- The End of Reality -- The Hype Machine -- Your Brain on Social Media -- A Network's Gravity is Proportional to Its Mass -- Personalized Mass Persuasion -- Hypersocialization -- Strategies for a Hypersocialized World -- The Attention Economy and the Tyranny of Trends -- The Wisdom and Madness of Crowds -- Social Media's Promise Is Also Its Peril -- Building a Better Hype Machine.

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Date

22. 1.2022 14:01:14