OutdoorSent: Sentiment Analysis of Urban Outdoor Images by Using Semantic and Deep Features

by   Wyverson B. de Oliveira, et al.

Opinion mining in outdoor images posted by users during day-to-day or leisure activities, for example, can provide valuable information to better understand urban areas. In this work, we propose a framework to classify the sentiment of outdoor images shared by users on social networks. We compare the performance of state-of-the-art ConvNet architectures, namely, VGG-16, Resnet50, and InceptionV3, as well as one specifically designed for sentiment analysis. The combination of such classifiers, a strategy known as ensemble, is also considered. We also use different experimental setups to evaluate how the merging of deep features and semantic information derived from the scene attributes can improve classification performance. The evaluation explores a novel dataset, namely OutdoorSent, of geolocalized urban outdoor images extracted from Instagram related to three sentiment polarities (positive, negative, and neutral), as well as another dataset publicly available (DeepSent). We observe that the incorporation of knowledge related to semantics features tend to improve the accuracy of low-complex ConvNet architectures. Furthermore, we also demonstrated the applicability of our results in the city of Chicago, United States, showing that they can help to understand the subjective characteristics of different areas of the city. For instance, particular areas of the city tend to concentrate more images of a specific class of sentiment. The ConvNet architectures, trained models, and the proposed outdoor image dataset will be publicly available at http://dainf.ct.utfpr.edu.br/outdoorsent.


page 7

page 10

page 12

page 13

page 16

page 17

page 18

page 19


OutdoorSent: Can Semantic Features Help Deep Learning in Sentiment Analysis of Outdoor Images?

Opinion mining in outdoor images posted by users during day-to-day or le...

Automatic Extraction of Urban Outdoor Perception from Geolocated Free-Texts

The automatic extraction of urban perception shared by people on locatio...

Sentiment Classification using Images and Label Embeddings

In this project we analysed how much semantic information images carry, ...

Language Independent Sentiment Analysis of theShukran Social Network Using Apache Spark

This paper describes theShukran Sentiment Analysis system. theShukran is...

When Saliency Meets Sentiment: Understanding How Image Content Invokes Emotion and Sentiment

Sentiment analysis is crucial for extracting social signals from social ...

Sentiment Classification using N-gram IDF and Automated Machine Learning

We propose a sentiment classification method with a general machine lear...

Sentiment Classification in Bangla Textual Content: A Comparative Study

Sentiment analysis has been widely used to understand our views on socia...