TY - GEN
T1 - Weaponizing the Wall
T2 - 16th International Conference on Social Networks Analysis and Mining, ASONAM 2024
AU - Singh, Daman Deep
AU - Chauhan, Gaurav
AU - Nguyen, Minh Kha
AU - Goga, Oana
AU - Chakraborty, Abhijnan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - A large fraction of people today consume most of their news online, and social media platforms like Facebook play a significant role in directing traffic to news articles. While news organizations often use Facebook advertising to drive traffic to their websites, this practice can inadvertently lead to biases in what articles users get exposed to, or worse, could be used as a mechanism for manipulation. In this work, we examine the impact of sponsored news on Facebook on the dissemination of propaganda. Propaganda is a method of persuasion that is frequently employed to advance some sort of goal, such as a personal, political, or business objective. By analyzing 17 Million+ Facebook posts and 6 Million sponsored advertisements gathered over 182 days, we observe that advertisers of all kinds, including politicians, media houses, and commercial corporations, publish thousands of ads/boosted posts every day on Facebook. However, Facebook does not include advertisements from news organizations in their public ad archive, even when these ads address political and social issues. This exemption places news organizations in a unique position where they can publish paid political opinions without any transparency requirements. The risk is that news organizations or other third-party interest groups can selectively promote news articles that support their agenda, giving these ads an appearance of legitimacy because they link to established news sites. In this paper, we explore how such sponsored news on Facebook can be a powerful tool for spreading propaganda. Through this work, we hope to raise awareness among users about the potential biases in sponsored news and the need to critically evaluate the information they see on Facebook.
AB - A large fraction of people today consume most of their news online, and social media platforms like Facebook play a significant role in directing traffic to news articles. While news organizations often use Facebook advertising to drive traffic to their websites, this practice can inadvertently lead to biases in what articles users get exposed to, or worse, could be used as a mechanism for manipulation. In this work, we examine the impact of sponsored news on Facebook on the dissemination of propaganda. Propaganda is a method of persuasion that is frequently employed to advance some sort of goal, such as a personal, political, or business objective. By analyzing 17 Million+ Facebook posts and 6 Million sponsored advertisements gathered over 182 days, we observe that advertisers of all kinds, including politicians, media houses, and commercial corporations, publish thousands of ads/boosted posts every day on Facebook. However, Facebook does not include advertisements from news organizations in their public ad archive, even when these ads address political and social issues. This exemption places news organizations in a unique position where they can publish paid political opinions without any transparency requirements. The risk is that news organizations or other third-party interest groups can selectively promote news articles that support their agenda, giving these ads an appearance of legitimacy because they link to established news sites. In this paper, we explore how such sponsored news on Facebook can be a powerful tool for spreading propaganda. Through this work, we hope to raise awareness among users about the potential biases in sponsored news and the need to critically evaluate the information they see on Facebook.
KW - Facebook Ads
KW - Propaganda Detection
KW - Sponsored News
UR - https://www.scopus.com/pages/publications/85218472453
U2 - 10.1007/978-3-031-78541-2_27
DO - 10.1007/978-3-031-78541-2_27
M3 - Conference contribution
AN - SCOPUS:85218472453
SN - 9783031785405
T3 - Lecture Notes in Computer Science
SP - 438
EP - 454
BT - Social Networks Analysis and Mining - 16th International Conference, ASONAM 2024, Proceedings
A2 - Aiello, Luca Maria
A2 - Chakraborty, Tanmoy
A2 - Gaito, Sabrina
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 2 September 2024 through 5 September 2024
ER -