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Analysis of Filipino Mood Swings within a Day using Tweets

Topics: Analytics as a Service (AaaS) for any Types of Analytics; Analytics, Intelligence and Knowledge Engineering; Big Data Algorithm, Methodology, Business Models and Challenges; Social Science and Implications for Big Data; Software Engineering for Big Data Analytics; User Evaluations and Case Studies

Authors: Rodalyn Balajadia ; Vincent Maglambayan and Maria Pulido

Affiliation: Department of Physics, Mapúa University, Manila City, 1002 and Philippines

ISBN: 978-989-758-369-8

Keyword(s): Data Analytics, Big Data Algorithm, Social Science and Implications for Big Data, APIs, User Evaluations and Case Studies, Microblogging, Twitter, Opinion Mining.

Abstract: We infer moods and how they vary with time using a dataset from the social media application Twitter. We used Python text mining techniques to gather all tweets originating from the Philippines within a span of 24 hours. From the dataset of around 130,000 tweets, we gathered the highest-frequency words and filtered out neutral words to come up with words that imply mood levels. We then plotted the density of keyword usage with respect to time, distinguishing between positive and negative moods. Our initial results of positive mood and negative mood trends are consistent with published studies regarding microblogging mood scales. The emergence of Big Data and the Internet of Things has greatly amplifed our ability not only to express ourselves but to understand each other.

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Paper citation in several formats:
Balajadia, R.; Maglambayan, V. and Pulido, Maria Teresa R. (2019). Analysis of Filipino Mood Swings within a Day using Tweets.In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-369-8, pages 364-369. DOI: 10.5220/0007749803640369

@conference{iotbds19,
author={Rodalyn A. Balajadia. and Vincent Louie L. Maglambayan. and Pulido, Maria Teresa R.},
title={Analysis of Filipino Mood Swings within a Day using Tweets},
booktitle={Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2019},
pages={364-369},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007749803640369},
isbn={978-989-758-369-8},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Analysis of Filipino Mood Swings within a Day using Tweets
SN - 978-989-758-369-8
AU - Balajadia, R.
AU - Maglambayan, V.
AU - Pulido, Maria Teresa R.
PY - 2019
SP - 364
EP - 369
DO - 10.5220/0007749803640369

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