Physical Sciences and Mathematics Commons^™

Identifying And Characterizing Alternative News Media On Facebook, Samuel S. Guimaraes, Julia C. S. Reis, Lucas Lima, Filipe N. Ribeiro, Marisa Vasconcelos, Jisun An, Haewoon Kwak, Fabricio Benevenuto

Research Collection School Of Computing and Information Systems

As Internet users increasingly rely on social media sites to receive news, they are faced with a bewildering number of news media choices. For example, thousands of Facebook pages today are registered and categorized as some form of news media outlets. This situation boosted the so-called independent journalism, also known as alternative news media. Identifying and characterizing all the news pages that play an important role in news dissemination is key for understanding the news ecosystems of a country. In this work, we propose a graph-based semi-supervised method to measure the political bias of pages on most countries and show …

Real-Time Tracking And Mining Of Users’ Actions Over Social Media, Ejub Kajan, Noura Faci, Zakaria Maamar, Mohamed Sellami, Emir Ugljanin, Hamamache Kheddouci, Dragan H. Stojanović, Djamal Benslimane

All Works

© 2020, ComSIS Consortium. All rights reserved. With the advent of Web 2.0 technologies and social media, companies are actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about …

View, Like, Comment, Post: Analyzing User Engagement By Topic At 4 Levels Across 5 Social Media Platforms For 53 News Organizations, Kholoud K. Aldous, Jisun An, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We evaluate the effects of the topics of social media posts on audiences across five social media platforms (i.e., Facebook, Instagram, Twitter, YouTube, and Reddit) at four levels of user engagement. We collected 3,163,373 social posts from 53 news organizations across five platforms during an 8month period. We analyzed the differences in news organization platform strategies by focusing on topic variations by organization and the corresponding effect on user engagement at four levels. Findings show that topic distribution varies by platform, although there are some topics that are popular across most platforms. User engagement levels vary both by topics and …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

Diversity In Online Advertising: A Case Study Of 69 Brands On Social Media, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Lack of diversity in advertising is a long-standing problem. Despite growing cultural awareness and missed business opportunities, many minorities remain under- or inappropriately represented in advertising. Previous research has studied how people react to culturally embedded ads, but such work focused mostly on print media or television using lab experiments. In this work, we look at diversity in content posted by 69 U.S. brands on two social media platforms, Instagram and Facebook. Using face detection technology, we infer the gender, race, and age of both the faces in the ads and of the users engaging with ads. Using this dataset, …

Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Social media, as a major platform to disseminate information, has changed the way users and communities contribute content. In this paper, we aim to study content modifications on public Facebook pages operated by news media, community groups, and bloggers. We also study the possible reasons behind them, and their effects on user interaction. We conducted a detailed study of Content Censorship (CC) and Content Edit (CE) in Facebook using a detailed longitudinal dataset consisting of 57 public Facebook pages over 3 weeks covering 145,955 posts and 9,379,200 comments. We detected many CC and CE activities between 28% and 56% of …

Flooding In The Media, Jeremy Wheeler

July 24, 2015: Communicating Frequent Flooding

No abstract provided.

Using Statistical Methods To Determine Geolocation Via Twitter, Christopher M. Wright

Masters Theses & Specialist Projects

With the ever expanding usage of social media websites such as Twitter, it is possible to use statistical inquires to form a geographic location of a person using solely the content of their tweets. According to a study done in 2010, Zhiyuan Cheng, was able to detect a location of a Twitter user within 100 miles of their actual location 51% of the time. While this may seem like an already significant find, this study was done while Twitter was still finding its ground to stand on. In 2010, Twitter had 75 million unique users registered, as of March 2013, …

What You Want Is Not What You Get: Predicting Sharing Policies For Text-Based Content On Facebook, Arunesh Sinha, Li Yan, Lujo Bauer

Research Collection Lee Kong Chian School Of Business

As the amount of content users publish on social networking sites rises, so do the danger and costs of inadvertently sharing content with an unintended audience. Studies repeatedly show that users frequently misconfigure their policies or misunderstand the privacy features offered by social networks. A way to mitigate these problems is to develop automated tools to assist users in correctly setting their policy. This paper explores the viability of one such approach: we examine the extent to which machine learning can be used to deduce users' sharing preferences for content posted on Facebook. To generate data on which to evaluate …

Fragmented Social Media: A Look Into Selective Exposure To Political News, Jisun An, Daniele Quercia, Jon Crowcroft

Research Collection School Of Computing and Information Systems

The hypothesis of selective exposure assumes that people crave like-minded information and eschew information that conflicts with their beliefs, and that has negative consequences on political life. Yet, despite decades of research, this hypothesis remains theoretically promising but empirically difficult to test. We look into news articles shared on Facebook and examine whether selective exposure exists or not in social media. We find a concrete evidence for a tendency that users predominantly share like-minded news articles and avoid conflicting ones, and partisans are more likely to do that. Building tools to counter partisanship on social media would require the ability …

Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao

Research Collection School Of Computing and Information Systems

Most social networking platforms protect user's private information by limiting access to it to a small group of members, typically friends of the user, while allowing (virtually) everyone's access to the user's public data. In this paper, we exploit public data available on Facebook to infer users' undisclosed interests on their profile pages. In particular, we infer their undisclosed interests from the public data fetched using Graph APIs provided by Facebook. We demonstrate that simply liking a Facebook page does not corroborate that the user is interested in the page. Instead, we perform sentiment-oriented mining on various attributes of a …