Physical Sciences and Mathematics Commons^™

Bounded Confidence: How Ai Could Exacerbate Social Media’S Homophily Problem, Dylan Weber, Scott Atran, Rich Davis

New England Journal of Public Policy

The advent of the Internet was heralded as a revolutionary development in the democratization of information. It has emerged, however, that online discourse on social media tends to narrow the information landscape of its users. This dynamic is driven by the propensity of the network structure of social media to tend toward homophily; users strongly prefer to interact with content and other users that are similar to them. We review the considerable evidence for the ubiquity of homophily in social media, discuss some possible mechanisms for this phenomenon, and present some observed and hypothesized effects. We also discuss how the …

Estimating Homophily In Social Networks Using Dyadic Predictions, George Berry, Antonio Sirianni, Ingmar Weber, Jisun An, Michael Macy

Research Collection School Of Computing and Information Systems

Predictions of node categories are commonly used to estimate homophily and other relational properties in networks. However, little is known about the validity of using predictions for this task. We show that estimating homophily in a network is a problem of predicting categories of dyads (edges) in the graph. Homophily estimates are unbiased when predictions of dyad categories are unbiased. Node-level prediction models, such as the use of names to classify ethnicity or gender, do not generally produce unbiased predictions of dyad categories and therefore produce biased homophily estimates. Bias comes from three sources: sampling bias, correlation between model errors …

Raising Funds In The Era Of Digital Economy, Deserina Sulaeman

Dissertations and Theses Collection (Open Access)

The rapid advancement in technology and internet penetration have substantially increased the number of economic transactions conducted online. Platforms that connect economic agents play an important role in this digital economy. The unbridled proliferation of digital platforms calls for a closer examination of the factors that could affect the welfare of the increasing number of economic agents who participate in them.

This dissertation examines the factors that could affect the welfare of agents using the setting of a crowdfunding platform where fundraisers develop campaigns to solicit funding from potential donors. These factors can be broadly categorized into three distinct groups: …

A Study On The Friendship Paradox – Quantitative Analysis And Relationship With Assortative Mixing, Siddharth Pal, Feng Yu, Yitzchak Novick, Ananthram Swami, Amotz Bar-Noy

Lander College of Arts and Sciences Publications and Research

The friendship paradox is the observation that friends of individuals tend to have more friends or be more popular than the individuals themselves. In this work, we first study local metrics to capture the strength of the paradox and the direction of the paradox from the perspective of individual nodes, i.e., an indication of whether the individual is more or less popular than its friends. These local metrics are aggregated, and global metrics are proposed to express the phenomenon on a network-wide level. Theoretical results show that the defined metrics are well-behaved enough to capture the friendship paradox. We also …

Exploiting Contextual Information For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The problem of fine-grained tweet geolocation is to link tweets to their posting venues. We solve this in a learning to rank framework by ranking candidate venues given a test tweet. The problem is challenging as tweets are short and the vast majority are non-geocoded, meaning information is sparse for building models. Nonetheless, although only a small fraction of tweets are geocoded, we find that they are posted by a substantial proportion of users. Essentially, such users have location history data. Along with tweet posting time, these serve as additional contextual information for geolocation. In designing our geolocation models, we …

Collaboration Trumps Homophily In Urban Mobile Crowdsourcing, Thivya Kandappu, Archan Misra, Randy Tandriansyah

Research Collection School Of Computing and Information Systems

This paper establishes the power of dynamic collaborative task completion among workers for urban mobile crowdsourcing. Collaboration is defined via the notion of peer referrals, whereby a worker who has accepted a location-specific task, but is unlikely to visit that location, offloads the task to a willing friend. Such a collaborative framework might be particularly useful for task bundles, especially for bundles that have higher geographic dispersion. The challenge, however, comes from the high similarity observed in the spatiotemporal pattern of task completion among friends. Using extensive real-world crowd-sourcing studies conducted over 7 weeks and 1000+ workers on a campus-based …

Collaboration Trumps Homophily In Urban Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Randy Tandriansyah Daratan

Research Collection School Of Computing and Information Systems

This paper establishes the power of dynamic collaborative task completion among workers for urban mobile crowdsourcing. Collaboration is defined via the notion of peer referrals, whereby a worker who has accepted a location-specific task, but is unlikely to visit that location, offloads the task to a willing friend. Such a collaborative framework might be particularly useful for task bundles, especially for bundles that have higher geographic dispersion. The challenge, however, comes from the high similarity observed in the spatiotemporal pattern of task completion among friends. Using extensive real-world crowd-sourcing studies conducted over 7 weeks and 1000+ workers on a campus-based …

Representation Learning For Homophilic Preferences, Trong T. Nguyen, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Users express their personal preferences through ratings, adoptions, and other consumption behaviors. We seek tolearn latent representations for user preferences from such behavioral data. One representation learning model that has been shown to be effective for large preference datasets is Restricted Boltzmann Machine (RBM). While homophily, or the tendency of friends to share their preferences at some level, is an established notion in sociology, thus far it has not yet been clearly demonstrated on RBM-based preference models. The question lies in how to appropriately incorporate social network into the architecture of RBM-based models for learning representations of preferences. In this …

Cross-Promotion In Social Media: Choosing The Right Allies, Tingting Song, Qian Tang

Research Collection School Of Computing and Information Systems

This paper investigates the strategic use of cross-promotion for content producers in social media. In particular, we study how a producer chooses other producers to cross-promote so as to maximize the expected benefits of them cross-promoting him/her in return. Theories on homophily effect and social influence suggest that cross-promoted producers are more likely to cross-promote the initiator in return when they are in the similar categories or share more common friends and when the initiator has higher status. However, the cross-promotion from producers of different categories and social groups (i.e., share fewer common friends) tend to benefit the initiator more. …

A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang

Research Collection School Of Computing and Information Systems

User attribute extraction on social media has gain considerable attention, while existing methods are mostly supervised which suffer great diffi- culty in insufficient gold standard data. In this paper, we validate a strong hypothesis based on homophily and adapt it to ensure the certainty of user attribute we extracted via weakly supervised propagation. Homophily, the theory which states that people who are similar tend to become friends, has been well studied in the setting of online social networks. When we focus on age attribute, based on this theory, online friends tend to have similar age. In this work, we take …

Evaluation And Assessment Of Recommenders Using Monte Carlo Simulation, Renato Costa, Luiz Fernando Capretz

Luiz Fernando Capretz

There have been various definitions, representations and derivations of trust in the context of recommender systems. This article presents a recommender predictive model based on collaborative filtering techniques that incorporate a fuzzy-driven quantifier, which includes two upmost relevant social phenomena parameters to address the vagueness inherent in the assessment of trust in social networks relationships. An experimental evaluation procedure utilizing a case study is conducted to analyze the overall predictive accuracy. These results show that the proposed methodology improves the performance of classical recommender approaches. Possible extensions are then outlined.

Twitter Influence And Cumulative Perceptions Of Extremist Support: A Case Study Of Geert Wilders, Gabrielle Blanquart, David M. Cook

Dr. David M Cook

The advent of Social media has changed the manner in which perceptions about power and information can be influenced. Twitter is used as a fast‐paced vehicle to deliver short, succinct pieces of information, creating the perception of acceptance, popularity and authority. In the case of extremist groups, Twitter is one of several avenues to create the perception of endorsement of values that would otherwise gain less prominence through mainstream media. This study examines the use of Twitter in augmenting the status and reputation of anti‐Islam and anti‐immigration policy through the controlled release of social media information bursts. The paper demonstrates …

Birds Of A Feather Deceive Together: The Chicanery Of Multiplied Metadata, David M. Cook

Dr. David M Cook

Twitter Influence And Cumulative Perceptions Of Extremist Support: A Case Study Of Geert Wilders, Gabrielle Blanquart, David M. Cook

Australian Counter Terrorism Conference

The advent of Social media has changed the manner in which perceptions about power and information can be influenced. Twitter is used as a fast‐paced vehicle to deliver short, succinct pieces of information, creating the perception of acceptance, popularity and authority. In the case of extremist groups, Twitter is one of several avenues to create the perception of endorsement of values that would otherwise gain less prominence through mainstream media. This study examines the use of Twitter in augmenting the status and reputation of anti‐Islam and anti‐immigration policy through the controlled release of social media information bursts. The paper demonstrates …

Evaluation And Assessment Of Recommenders Using Monte Carlo Simulation, Renato Costa, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

There have been various definitions, representations and derivations of trust in the context of recommender systems. This article presents a recommender predictive model based on collaborative filtering techniques that incorporate a fuzzy-driven quantifier, which includes two upmost relevant social phenomena parameters to address the vagueness inherent in the assessment of trust in social networks relationships. An experimental evaluation procedure utilizing a case study is conducted to analyze the overall predictive accuracy. These results show that the proposed methodology improves the performance of classical recommender approaches. Possible extensions are then outlined.

What Is Twitter, A Social Network Or A News Media?, Haewoon Kwak, Changhyun Lee, Hosung: Moon Park

Research Collection School Of Computing and Information Systems

Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing.We have crawled the entire Twitter site and obtained 41.7 million user profiles, 1.47 billion social relations, 4,262 trending topics, and 106 million tweets. In its follower-following topology analysis we have found a non-power-law follower distribution, a short …

Homophily In The Digital World: A Livejournal Case Study, Hady W. Lauw, John C. Shafer, Rakesh Agrawal, Alexandros Ntoulas

Research Collection School Of Computing and Information Systems

Are two users more likely to be friends if they share common interests? Are two users more likely to share common interests if they're friends? The authors study the phenomenon of homophily in the digital world by answering these central questions. Unlike the physical world, the digital world doesn't impose any geographic or organizational constraints on friendships. So, although online friends might share common interests, a priori there's no reason to believe that two users with common interests are more likely to be friends. Using data from LiveJournal, the authors show that the answer to both questions is yes.