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We feel fine and searching the emotional web

Published: 09 February 2011 Publication History

Abstract

We present We Feel Fine, an emotional search engine and web-based artwork whose mission is to collect the world's emotions to help people better understand themselves and others. We Feel Fine continuously crawls blogs, microblogs, and social networking sites, extracting sentences that include the words "I feel" or "I am feeling", as well as the gender, age, and location of the people authoring those sentences. The We Feel Fine search interface allows users to search or browse over the resulting sentence-level index, asking questions such as "How did young people in Ohio feel when Obama was elected?" While most research in sentiment analysis focuses on algorithms for extraction and classification of sentiment about given topics, we focus instead on building an interface that provides an engaging means of qualitative exploration of emotional data, and a flexible data collection and serving architecture that enables an ecosystem of data analysis applications. We use our observations on the usage of We Feel Fine to suggest a class of visualizations called Experiential Data Visualization, which focus on immersive item-level interaction with data. We also discuss the implications of such visualizations for crowdsourcing qualitative research in the social sciences.

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cover image ACM Conferences
WSDM '11: Proceedings of the fourth ACM international conference on Web search and data mining
February 2011
870 pages
ISBN:9781450304931
DOI:10.1145/1935826
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 February 2011

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  1. search
  2. sentiment analysis
  3. social media

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WSDM '11 Paper Acceptance Rate 83 of 372 submissions, 22%;
Overall Acceptance Rate 498 of 2,863 submissions, 17%

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  • (2025)Using Sentiment Analysis to Construe Tweets and the Controversy During the 2020 American Presidential ElectionsProceedings of International Conference on Communication and Computational Technologies10.1007/978-981-97-7426-5_34(449-459)Online publication date: 19-Jan-2025
  • (2024)Linguistic based emotion analysis using softmax over time attention mechanismPLOS ONE10.1371/journal.pone.030133619:4(e0301336)Online publication date: 16-Apr-2024
  • (2024)Sarcasm‐based tweet‐level stress detectionExpert Systems10.1111/exsy.1353441:4Online publication date: 10-Jan-2024
  • (2024)Sentiment Analysis Principle Technical Approach on Online Social Network Data Using CNN for Detection of StressProceedings of Fifth International Conference on Computer and Communication Technologies10.1007/978-981-99-9704-6_37(401-410)Online publication date: 14-Feb-2024
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  • (2023)Order-Sensitivity Sentiment dictionary of word sequences containing intensifiersMultimedia Tools and Applications10.1007/s11042-023-17734-3Online publication date: 11-Dec-2023
  • (2023)Deriving Pipeline for Emergency Services Using Natural Language Processing TechniquesProceedings of International Conference on Recent Trends in Computing10.1007/978-981-19-8825-7_49(573-580)Online publication date: 21-Mar-2023
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  • (2022)Sentiment Analysis on Online Reviews using Machine Learning and NLTK2022 6th International Conference on Trends in Electronics and Informatics (ICOEI)10.1109/ICOEI53556.2022.9776850(1183-1189)Online publication date: 28-Apr-2022
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