Visual Sentiment Analysis

Sentiment Analysis of Urban Images by Using Semantic and Deep Features

Project Goal

The present study focuses on the understanding of the sentiment of urban images shared by users on social networks.

PerceptSent

Cesar R Lopes, Rodrigo Minetto, Myriam R Delgado, and Thiago H Silva. 2022. PerceptSent - Exploring Subjectivity in a Novel Dataset for Visual Sentiment Analysis. IEEE Transactions on Affective Computing - link to the paper

Data

PerceptSent Dataset: Composed of 500 images from Flickr, Instagram, and NYC311. A pool of five evaluators labelled all images as positive, slightly positive, neutral, slightly negative, and negative. Besides the sentiment opinion for each image, the dataset contains metadata concerning~ each evaluator --- age, gender, socio-economic strata, education, and psychological hints --- their perceptions, such as the presence of nature, violence, lack of maintenance, among others --- as well as independent scene objects annotated in the images.

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Code

The ConvNet architectures explored in this paer, trained models are available here.

OutdoorSent

Wyverson Bonasoli de Oliveira, Leyza Baldo Dorini, Rodrigo Minetto, and Thiago H. Silva. 2020. OutdoorSent: Sentiment Analysis of Urban Outdoor Images by Using Semantic and Deep Features ACM Trans. Inf. Syst. 38, 3, Article 23 (May 2020), 28 pages. Link to the paper

Data

OutdooSent Dataset: Composed of 1,950 outdoor images from Flickr. Each of them was labeled based on the evaluation of five different volunteers. Then, each image is labeled as Positive, Neutral, or Negative.