Topic modeling and sentiment analysis of global climate change tweets
Bibliographic Data
| ID | 4683900 |
|---|---|
| Authors | Biraj Dahal (0000-0003-1483-130X, Clemson University), Sathish A P Kumar (0000-0002-3162-2211, Coastal Carolina University, corresponding author), Zhenlong Li (0000-0002-8938-5466, University of South Carolina) |
| Year | 2019 |
| Volume | 9 |
| Issue | 1 |
| Publication date | 2019-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-019-0568-8 |
| OpenAlex | W2952214074 |
| Language | EN |
| Citations received | 61 |
| References cited | 23 |
Climate change · Data science · Geographic coordinate system · Geography · Information retrieval · Latent Dirichlet allocation · Political science · Politics · Public opinion · Sentiment analysis · Social media · Topic model · World Wide Web · Climate Change Communication and Perception · Complex Network Analysis Techniques · Computer Science · Opinion Dynamics and Social Influence · Artificial Intelligence
Sentiment Analysis of Weather-Related Tweets from Cities within Hot Climates
A Corpus-Assisted Discourse Analysis Case Study of Public Opinion on Climate Change in Malaysia
Using Social Media to Mine and Analyze Public Opinion Related to Covid-19 in China
On Recent Advances in Public Procurement
Aggregating narratives on oil and gas from opposing advocacy groups
Representation of environmental issues
A review of topic modeling methods
What We Ask about When We Ask about Quarantine? Content and Sentiment Analysis on Online Help-Seeking Posts during Covid-19 on a Q&A Platform in China
A Study of Public Attitudes toward Shanghai’s Image under the Influence of Covid-19
Tourists’ perceptions of climate
What Do Twitter Users Think about Climate Change? Characterization of Twitter Interactions Considering Geographical, Gender, and Account Typologies Perspectives
Topic modelling of public Twitter discourses, part bot, part active human user, on climate change and global warming
Exploring Philippine Presidents’ speeches
Political Response Analysis of Twitter/X Users Using Topic-Based Sentiment Analysis
Applying GIS and Text Mining Methods to Twitter Data to Explore the Spatiotemporal Patterns of Topics of Interest in Kuwait
Modelling and Analyzing the Semantic Evolution of Social Media User Behaviors during Disaster Events
Analysis of Geotagging Behavior
Response to critique of the paper
Spatial and sentiment analysis of public opinion toward Covid-19 pandemic using twitter data
Do typhoon disasters foster climate change concerns? Evidence from public discussions on social media in China
Spatio-temporal evolution of public opinion on urban flooding
Semantics-enriched spatiotemporal mapping of public risk perceptions for cultural heritage during radical events
Aware but not prepared
Climate Sentiment and Corporate Default Risk
Tracking public opinion about online education over Covid-19 in China
A computational approach to cryptocurrency marketing on social media
Approaches to improve preprocessing for Latent Dirichlet Allocation topic modeling
Return migration of German-affiliated researchers
Proactive social learning and green product consumption
Political Common Ground on Preserving Nature
Applications of machine learning and deep learning methods for climate change mitigation and adaptation
The Robot's “Myths of Nature”
Latent Dirichlet Allocation (LDA) topic models for Space Syntax studies on spatial experience
Impacto de la comunicación en Twitter en el movimiento ambientalista durante la COP15
Characterizing climate change sentiments in Alaska on social media
Critical Transitions in Ecosystems and Society. The Contribution of Sociological Systems Theory to the Analysis of Socio-Environmental Transformations
Fossil fuel companies' climate communication strategies
Lost in communication
Climate change discourse on Chinese social media
How Climate Movement Actors and News Media Frame Climate Change and Strike
Climate change on Twitter
Rural‐Urban Differences in the Determinants of Subjective Well‐Being Among X/Twitter Users in the United States
Green energy
Climate nags
Tweeting about the environment in a European campaign. Are candidates in the European Parliament elections responsive to citizens’ environmental concerns
Bridging the Ideological Divide
Unveiling global narratives of restoration policy
Vaccine hesitancy, parental concerns, and Covid-19 in a digital leisure context
Crisis talk
Normalising inhomogeneities in geo-social media data – a comparison of different measures
Deep learning based topic and sentiment analysis
An exploratory study of net zero discourse based on South Korean newspapers
Topic-based engagement analysis
Using natural language processing approaches to characterize professional experiences of child welfare workers
Sentiment is Not Stance
Identification of affective valence of Twitter generated sentiments during the Covid-19 outbreak
A performant deep learning model for sentiment analysis of climate change
The impact of political party/candidate on the election results from a sentiment analysis perspective using #AnambraDecides2017 tweets
Analyzing the sentiment correlation between regular tweets and retweets
Understanding the removal of precise geotagging in tweets
Automated Framing of Climate Change? The Role of Social Bots in the Twitter Climate Change Discourse During the 2019/2020 Australia Bushfires
Introduction to Information Retrieval
Predicting Elections with Twitter
Sentiment analysis algorithms and applications
A biterm topic model for short texts
Vader
Climate Change Sentiment on Twitter
The geography of Twitter topics in London
Exploring the Space of Topic Coherence Measures
Probabilistic topic models
What are we ‘tweeting’ about obesity? Mapping tweets with topic modeling and Geographic Information System
Public microblogging on climate change
| Unique citing works | 61 |
|---|---|
| Citations per year | 10,17 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 55 |