Open Access. Powered by Scholars. Published by Universities.®
Science and Technology Studies Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 22 of 22
Full-Text Articles in Science and Technology Studies
Arguing For Argument’S Sake? Exploring Public Conversations Around Climate Change On Twitter, Kennedy Mayfield-Smith, Alexa Lamm, Fallys Masambuka-Kanchewa, Abigail Borron, Jessica Holt
Arguing For Argument’S Sake? Exploring Public Conversations Around Climate Change On Twitter, Kennedy Mayfield-Smith, Alexa Lamm, Fallys Masambuka-Kanchewa, Abigail Borron, Jessica Holt
Journal of Applied Communications
Audience-facilitated information flow has become the new norm created by a public divergence from traditional media sources. Mobile device advancements and partnerships have changed how audiences view news media and the sources relied upon to obtain information. With these advancements, social media users have become primary information providers and information gatekeepers. Twitter specifically has become a news media platform for some based on its effectiveness in facilitating information flow and triggering reorganization as it provides a platform for collaboration and coordination. Despite widespread acceptance of the threat climate change poses by the scientific community, it is still a topic of …
How Misinformation Spreads Through Twitter, Mary Blankenship
How Misinformation Spreads Through Twitter, Mary Blankenship
Student Research
While living in the age of information, an inherent drawback to such high exposure to content lends itself to the precarious rise of misinformation. Whether it is called “alternative facts,” “fake news,” or just incorrect information, because of its pervasiveness in nearly every political and policy discussion, the spread of misinformation is seen as one of the greatest challenges to overcome in the 21st century. As new technologies emerge, a major piece of both content creation and the perpetuation of misinformation are social media platforms like Twitter, Facebook, and YouTube. As news events emerge, whether be a pandemic, a mass …
A Pilot Qualitative Case Study Of Agricultural And Natural Resources Scientists’ Twitter Usage For Engaging Public Audiences, Jamie Loizzo, Catherine Jones, Abby Steffen
A Pilot Qualitative Case Study Of Agricultural And Natural Resources Scientists’ Twitter Usage For Engaging Public Audiences, Jamie Loizzo, Catherine Jones, Abby Steffen
Journal of Applied Communications
Scientists are frequently asked to broadly share their expertise and research with a variety of audiences, beyond typical academic circles in their home disciplines. That could include developing community engagement programs, school outreach, leveraging online social networks, and other activities. The purpose of this study was to examine U.S. agricultural and natural resources (ANR) scientists’ typical science communication channels, their experiences utilizing Twitter for sharing their knowledge, research, and engaging in online public science discussion. Diffusion of Innovations theory and the model of science in-reach versus outreach guided this study. Researchers used a qualitative case study design. Data collection included …
The Affective Politics Of Twitter, Johnathan C. Flowers
The Affective Politics Of Twitter, Johnathan C. Flowers
Computer Ethics - Philosophical Enquiry (CEPE) Proceedings
Given the increasing encroachment of Twitter into offline experience, it has become necessary to look beyond the formation of identity in online spaces to the ways in which identities surface through the formation of affective communities organized through the use of technocultural assemblages, or the platforms, algorithms, and digital networks through which affect circulates in an online space. This essay focuses on the microblogging website Twitter as one such technocultural assemblage whose hashtag functionality allows for the circulation of affect among bodies which “surface” within the affective communities organized on Twitter through their alignment with and orientation by hashtags which …
Social Media: On Tech-Caves, Virtual Panopticism, And The Science Fiction-Like State In Which We Unwittingly Find Ourselves, Michael Major
Social Media: On Tech-Caves, Virtual Panopticism, And The Science Fiction-Like State In Which We Unwittingly Find Ourselves, Michael Major
Theses
Making use of three historic philosophical thought experiments, this paper blends psychological perspectives with philosophical reasoning to show how social media is corrupting our perception of reality, the result of which is ultimately detrimental to society as a whole. This is accomplished by first using Plato’s “Allegory of the Cave” to analyze and discuss the ways in which social media is limiting humanity’s access to real knowledge. Next, Michel Foucault’s analysis of punishment in its social context, Discipline and Punish, is used to discuss the ways in which social media is adversely affecting our behavior. Finally, Robert Nozick’s “Experience …
Delving Into The Specificity Of Instructional Guidance In Social Media-Supported Learning Environments, Tian Luo
STEMPS Faculty Publications
Aim/Purpose: This study investigates the variations in student participation patterns across different types of instructional activities, learning modes, and with different instructional guidance approaches. In the current study, different variables, modes of learning (guided versus unguided), and types of guidance (social versus cognitive) were manipulated in a series of microblogging-supported collaborative learning tasks to examine to what extent and in which aspects instructional guidance affects the effectiveness and student perception of microblogging-supported learning.
Background: Despite the overwhelming agreement on the importance of instructional guidance in microblogging-supported learning environments, very few studies have been done to examine the specificity of guidance, …
Social Health Signals, Ashutosh Sopan Jadhav, Swapnil Soni, Amit P. Sheth
Social Health Signals, Ashutosh Sopan Jadhav, Swapnil Soni, Amit P. Sheth
Kno.e.sis Publications
Recently Twitter, has emerged as one of the primary medium for sharing and seeking of the latest information related to variety of the topics including health information. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, identification of useful information from the deluge of tweets is one of the major challenge. Twitter search is limited to keyword based techniques to retrieve information for a given query and sometimes the results do not contain real-time information. Moreover, …
Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni
Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni
Kno.e.sis Publications
With the advent of the web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these online services to share and seek health real-time information has in- creased exponentially. OHIS use web search engines or microblogging search services to seek out latest, relevant as well as reliable health in- formation. When OHIS turn to microblogging search services to search real-time content, trends and breaking news, etc. the search results are not promising. Two major challenges exist in the current microblogging search engines are keyword based techniques and results do not contain real-time information. To address these challenges, …
Domain Specific Document Retrieval Framework On Near Real-Time Social Health Data, Swapnil Soni
Domain Specific Document Retrieval Framework On Near Real-Time Social Health Data, Swapnil Soni
Kno.e.sis Publications
With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …
Knowledge Enabled Approach To Predict The Location Of Twitter Users, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Knowledge Enabled Approach To Predict The Location Of Twitter Users, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
Knowledge bases have been used to improve performance in applications ranging from web search and event detection to entity recognition and disambiguation. More recently, knowledge bases have been used to analyze social data. A key challenge in social data analysis has been the identification of the geographic location of online users in a social network such as Twitter. Existing approaches to predict the location of users, based on their tweets, rely solely on social media features or probabilistic language models. These approaches are supervised and require large training dataset of geo-tagged tweets to build their models. As most Twitter users …
Active Learning With Efficient Feature Weighting Methods For Improving Data Quality And Classification Accuracy, Justin Martineau, Lu Chen, Doreen Cheng, Amit P. Sheth
Active Learning With Efficient Feature Weighting Methods For Improving Data Quality And Classification Accuracy, Justin Martineau, Lu Chen, Doreen Cheng, Amit P. Sheth
Kno.e.sis Publications
Many machine learning datasets are noisy with a substantial number of mislabeled instances. This noise yields sub-optimal classification performance. In this paper we study a large, low quality annotated dataset, created quickly and cheaply using Amazon Mechanical Turk to crowdsource annotations. We describe computationally cheap feature weighting techniques and a novel non-linear distribution spreading algorithm that can be used to iteratively and interactively correcting mislabeled instances to significantly improve annotation quality at low cost. Eight different emotion extraction experiments on Twitter data demonstrate that our approach is just as effective as more computationally expensive techniques. Our techniques save a considerable …
Hierarchical Interest Graph From Tweets, Pavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit P. Sheth
Hierarchical Interest Graph From Tweets, Pavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit P. Sheth
Kno.e.sis Publications
Industry and researchers have identified numerous ways to monetize microblogs for personalization and recommendation. A common challenge across these different works is the identification of user interests. Although techniques have been developed to address this challenge, a flexible approach that spans multiple levels of granularity in user interests has not been forthcoming. In this work, we focus on exploiting hierarchical semantics of concepts to infer richer user interests expressed as a Hierarchical Interest Graph. To create such graphs, we utilize users' tweets to first ground potential user interests to structured background knowledge such as Wikipedia Category Graph. We then adapt …
Cursing In English On Twitter, Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth
Cursing In English On Twitter, Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of …
Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
The mining of user generated content in social media has proven very effective in domains ranging from personalization and recommendation systems to crisis management. The knowledge of online users locations makes their tweets more informative and adds another dimension to their analysis. Existing approaches to predict the location of Twitter users are purely data-driven and require large training data sets of geo-tagged tweets. The collection and modelling process of tweets can be time intensive. To overcome this drawback, we propose a novel knowledge based approach that does not require any training data. Our approach uses information in Wikipedia, about cities …
User Taglines: Alternative Presentations Of Expertise And Interest In Social Media, Hemant Purohit, Alex Dow, Omar Alonso, Lei Duan, Kevin Haas
User Taglines: Alternative Presentations Of Expertise And Interest In Social Media, Hemant Purohit, Alex Dow, Omar Alonso, Lei Duan, Kevin Haas
Kno.e.sis Publications
Web applications are increasingly showing recommended users from social media along with some descriptions, an attempt to show relevancy - why they are being shown. For example, Twitter search for a topical keyword shows expert twitterers on the side for 'whom to follow'. Google+ and Facebook also recommend users to follow or add to friend circle. Popular Internet newspaper- The Huffington Post shows Twitter influencers/ experts on the side of an article for authoritative relevant tweets. The state of the art shows user profile bios as summary for Twitter experts, but it has issues with length constraint imposed by user …
What Kind Of #Communication Is Twitter? A Psycholinguistic Perspective On Communication In Twitter For The Purpose Of Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach
What Kind Of #Communication Is Twitter? A Psycholinguistic Perspective On Communication In Twitter For The Purpose Of Emergency Coordination, Hemant Purohit, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach
Kno.e.sis Publications
The present research aims to detect coordinated citizen response within social media traffic to assist emergency response. We use domain-independent linguistic properties as the first step in narrowing the candidate set of messages for domain-dependent and computationally intensive analysis.
When Antitrust Met Facebook, Christopher S. Yoo
When Antitrust Met Facebook, Christopher S. Yoo
All Faculty Scholarship
Social networks are among the hottest phenomena on the Internet. Facebook eclipsed Google as the most visited website in both 2010 and 2011. Moreover, according to Nielsen estimates, as of the end of 2011 the average American spent nearly seven hours per month on Facebook, which is more time than they spent on Google, Yahoo!, YouTube, Microsoft, and Wikipedia combined. LinkedIn’s May 19, 2011 initial public offering (“IPO”) surpassed expectations, placing the value of the company at nearly $9 billion, and approximately a year later, its stock price had risen another 20 percent. Facebook followed suit a year later with …
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Kno.e.sis Publications
We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user behavioral patterns with respect to specific trending topics on Twitter. Going beyond previous efforts that have analyzed driving factors in whether and when a user will publish topic-relevant tweets, here we seek to predict the strength of content generation which allows more accurate understanding of Twitter users' behavior and more effective utilization of the online social network for diffusing information. Unlike traditional approaches, we consider multiple dimensions into one regression-based prediction framework covering network structure, user interaction, content characteristics and past activity. Experimental results on three large Twitter …
Extracting Diverse Sentiment Expressions With Target-Dependent Polarity From Twitter, Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth
Extracting Diverse Sentiment Expressions With Target-Dependent Polarity From Twitter, Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang, Amit P. Sheth
Kno.e.sis Publications
This study focuses on automatic extraction of sentiment expressions associated with given targets from Twitter. It addresses one of the key challenges in this work: Wide diversity and informal nature of sentiment expressions that cannot be trivially enumerated or captured using predefined lexical patterns.
Personalized Filtering Of The Twitter Stream, Pavan Kapanipathi, Fabrizio Orlandi, Amit P. Sheth, Alexandre Passant
Personalized Filtering Of The Twitter Stream, Pavan Kapanipathi, Fabrizio Orlandi, Amit P. Sheth, Alexandre Passant
Kno.e.sis Publications
With the rapid growth in users on social networks, there is a corresponding increase in user-generated content, in turn resulting in information overload. On Twitter, for example, users tend to receive uninterested information due to their non-overlapping interests from the people whom they follow. In this paper we present a Semantic Web approach to filter public tweets matching interests from personalized user profiles. Our approach includes automatic generation of multi-domain and personalized user profiles, filtering Twitter stream based on the generated profiles and delivering them in real-time. Given that users interests and personalization needs change with time, we also discuss …
Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth
Linked Open Social Signals, Pablo N. Mendes, Alexandre Passant, Pavan Kapanipathi, Amit P. Sheth
Kno.e.sis Publications
In this paper we discuss the collection, semantic annotation and analysis of real-time social signals from micro-blogging data. We focus on users interested in analyzing social signals collectively for sensemaking. Our proposal enables flexibility in selecting subsets for analysis, alleviating information overload. We define an architecture that is based on state-of-the-art Semantic Web technologies and a distributed publish subscribe protocol for real time communication. In addition, we discuss our method and application in a scenario related to the health care reform in the United States.
A Qualitative Examination Of Topical Tweet And Retweet Practices, Meenakshi Nagarajan, Hemant Purohit, Amit P. Sheth
A Qualitative Examination Of Topical Tweet And Retweet Practices, Meenakshi Nagarajan, Hemant Purohit, Amit P. Sheth
Kno.e.sis Publications
This work contributes to the study of retweet behavior on Twitter surrounding real-world events. We analyze over a million tweets pertaining to three events, present general tweet properties in such topical datasets and qualitatively analyze the properties of the retweet behavior surrounding the most tweeted/viral content pieces. Findings include a clear relationship between sparse/dense retweet patterns and the content and type of a tweet itself; suggesting the need to study content properties in link-based diffusion models.