Reaction Image Bank

Tumblr

Tumblr. Pure effervescent enrichment. Old internet energy. Home of the Reblogs. All the art you never knew you needed. All the fandoms you could wish for. Enough memes to knock out a moderately-sized mammal. Add to it or simply scroll through and soak it up.

Tumblr

Tumblr. Pure effervescent enrichment. Old internet energy. Home of the Reblogs. All the art you never knew you needed. All the fandoms you could wish for. Enough memes to knock out a moderately-sized mammal. Add to it or simply scroll through and soak it up.

Pasteboard - Uploaded Image

Pasteboard is the best way to share your screenshots and images online. It supports images of the formats JPEG, PNG, GIF, APNG and TIFF up to 5MB.

Pasteboard - Uploaded Image

Pasteboard is the best way to share your screenshots and images online. It supports images of the formats JPEG, PNG, GIF, APNG and TIFF up to 5MB.

Pasteboard - Uploaded Image

Pasteboard is the best way to share your screenshots and images online. It supports images of the formats JPEG, PNG, GIF, APNG and TIFF up to 5MB.

Pasteboard - Uploaded Image

Pasteboard is the best way to share your screenshots and images online. It supports images of the formats JPEG, PNG, GIF, APNG and TIFF up to 5MB.

Black Meme: A History of the Images that Make Us

A History of the Images that Make Us

Meta’s going to put AI-generated images in your Facebook and Instagram feeds

Facebook and Instagram feeds are about to get messier.

AMMeBa: A Large-Scale Survey and Dataset of Media-Based Misinformation In-The-Wild

The prevalence and harms of online misinformation is a perennial concern for internet platforms, institutions and society at large. Over time, information shared online has become more media-heavy and misinformation has readily adapted to these new modalities. The rise of generative AI-based tools, which provide widely-accessible methods for synthesizing realistic audio, images, video and human-like text, have amplified these concerns. Despite intense public interest and significant press coverage, quantitative information on the prevalence and modality of media-based misinformation remains scarce. Here, we present the results of a two-year study using human raters to annotate online media-based misinformation, mostly focusing on images, based on claims assessed in a large sample of publicly-accessible fact checks with the ClaimReview markup. We present an image typology, designed to capture aspects of the image and manipulation relevant to the image's role in the misinformation claim. We visualize the distribution of these types over time. We show the rise of generative AI-based content in misinformation claims, and that its commonality is a relatively recent phenomenon, occurring significantly after heavy press coverage. We also show "simple" methods dominated historically, particularly context manipulations, and continued to hold a majority as of the end of data collection in November 2023. The dataset, Annotated Misinformation, Media-Based (AMMeBa), is publicly-available, and we hope that these data will serve as both a means of evaluating mitigation methods in a realistic setting and as a first-of-its-kind census of the types and modalities of online misinformation.

AMMeBa: A Large-Scale Survey and Dataset of Media-Based Misinformation In-The-Wild

The prevalence and harms of online misinformation is a perennial concern for internet platforms, institutions and society at large. Over time, information shared online has become more media-heavy and misinformation has readily adapted to these new modalities. The rise of generative AI-based tools, which provide widely-accessible methods for synthesizing realistic audio, images, video and human-like text, have amplified these concerns. Despite intense public interest and significant press coverage, quantitative information on the prevalence and modality of media-based misinformation remains scarce. Here, we present the results of a two-year study using human raters to annotate online media-based misinformation, mostly focusing on images, based on claims assessed in a large sample of publicly-accessible fact checks with the ClaimReview markup. We present an image typology, designed to capture aspects of the image and manipulation relevant to the image's role in the misinformation claim. We visualize the distribution of these types over time. We show the rise of generative AI-based content in misinformation claims, and that its commonality is a relatively recent phenomenon, occurring significantly after heavy press coverage. We also show "simple" methods dominated historically, particularly context manipulations, and continued to hold a majority as of the end of data collection in November 2023. The dataset, Annotated Misinformation, Media-Based (AMMeBa), is publicly-available, and we hope that these data will serve as both a means of evaluating mitigation methods in a realistic setting and as a first-of-its-kind census of the types and modalities of online misinformation.

Memes in Digital Culture

Taking “Gangnam Style” seriously: what Internet memes can tell us about digital culture.In December 2012, the exuberant video “Gangnam Style” became the fi

Text to Image Leaderboard - Top AI Image Models

Find the best Text to Image models, see rankings from blind votes, and compare quality, generation speed, and price in one leaderboard.