TTLocVis: A Twitter Topic Location Visualization Package

Kant, Gillian; Weisser, Christoph; Säfken, Benjamin

doi:10.21105/joss.02507

Cited by 15 publications

(8 citation statements)

References 4 publications

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“…There are limits to our methodological approach and application. Firstly, due to the comparative nature of the methods we suggested, our experimentation did not fully employ some recent methods that complement LDA, such as hashtag-pooling (Mehrotra et al 2013;Kant et al 2020). Hashtag-pooling treats hashtags as topical markers, indicating the context or core idea of a tweet, which may further improve LDA modeling quality.…”

Section: Discussionmentioning

confidence: 99%

Cross-platform comparison of framed topics in Twitter and Weibo: machine learning approaches to social media text mining

Yang

Hsu

Löfgren

et al. 2021

Soc. Netw. Anal. Min.

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While the salience of social media platforms on modern interactive communication between diverse social actors has been demonstrated, less academic attention has been paid to comparisons between framed topics and user interactions across social media platforms, such as Twitter and Weibo. This article suggests text mining and natural language processing tools for cross-platform comparative social media studies, based on Latent Dirichlet Allocation (LDA) and social network analysis. This study illustrates how the suggested topic models and data processing algorithms can be applied to a real-life example (U.S.-China trade war discourse on social media), and experimented the methods on social media text mining data, revealing differences between user interactions on Twitter, predominantly "Western," and Weibo, largely representing Chinesespeaking users. We discuss the strengths and weaknesses of the suggested machine learning algorithms for comparative social media studies.

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Section: Discussionmentioning

confidence: 99%

Cross-platform comparison of framed topics in Twitter and Weibo: machine learning approaches to social media text mining

Yang

Hsu

Löfgren

et al. 2021

Soc. Netw. Anal. Min.

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“…Considering the need for transparency, accountability and public understanding, visualizing public participation data without usability evidence is not enough. On the one hand, recent studies have shown the effectiveness of modeling and visualizing public opinion, but mostly on informal settings and social media (Steinskog, Therkelsen & and Gambäck, 2017;Yu, Xu, Wang & Ni, 2019;Kant, Weisser & Säfken, 2020). On the other hand, the assessment of visualization strategies have often lacked a more comprehensive operationalization of usability and focused mostly on effectiveness.…”

Section: Discussionmentioning

confidence: 99%

“…In conclusion, several advances have been made in modeling and visualizing public opinion. However, recent studies tend to focus mostly on social media opinion analysis (Steinskog, Therkelsen & and Gambäck, 2017;Yu, Xu, Wang & Ni, 2019;Kant, Weisser & Säfken, 2020). The modeling and visualization of opinions from institutional citizen participation' instances is still missing more attention (Mukherjee, 2019).…”

Section: Usability As An Evaluation Methods Of Topic Visualization Interfacesmentioning

confidence: 99%

Remote Usability Assessment of Topic Visualization Interfaces with Public Participation Data: A Case Study

Yovanovic

Goñi

Miranda

2021

JeDEM

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Citizen participation often faces challenges of transparency and accountability. Visualizations’s usability becomes key for public consultation activities. The tree map is frequently used to disseminate data and to give it back to the population. The purpose of this study is to understand how tree maps and stacked barcharts differ in terms of effectiveness, efficiency, and satisfaction in tasks, like solving topic categorization and comparison analysis tasks. An experimental design was used to examine user performance based on a task-based usability test. 34 participants interacted remotely with data visualizations from an open 2016 participatory constitution-making process. The ANOVA showed that stacked barcharts work significantly better for comparison tasks than the tree map, but there are no significant differences in regards to categorization tasks. Public participation initiatives should first determine what cognitive operations their users perform before deciding which visualization interfaces will be more useful for the intended public.

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“…By applying pooling, Tweets can be used to build coherent LDA topic models. For Tweets, Kant et al (2020) provides a pooling implementation that uses the hashtags of Tweets. In Twitmo, we implemented hashtag pooling as proposed by Mehrotra et al (2013).…”

Section: Pseudo-document Generationmentioning

confidence: 99%

Twitmo: A Twitter Data Topic Modeling and Visualization Package for R

Buchmüller¹,

Kant²,

Weisser³

et al. 2022

Preprint

Self Cite

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We present Twitmo, a package that provides a broad range of methods to collect, pre-process, analyze and visualize geo-tagged Twitter data. Twitmo enables the user to collect geo-tagged Tweets from Twitter and and provides a comprehensive and user-friendly toolbox to generate topic distributions from Latent Dirichlet Allocations (LDA), correlated topic models (CTM) and structural topic models (STM). Functions are included for pre-processing of text, model building and prediction. In addition, one of the innovations of the package is the automatic pooling of Tweets into longer pseudo-documents using hashtags and cosine similarities for better topic coherence (Mehrotra et al., 2013). The package additionally comes with functionality to visualize collected data sets and fitted models in static as well as interactive ways and offers built-in support for model visualizations via LDAvis providing great convenience for researchers in this area. The Twitmo package is an innovative toolbox that can be used to analyze public discourse of various topics, political parties or persons of interest in space and time.

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TTLocVis: A Twitter Topic Location Visualization Package

Cited by 15 publications

References 4 publications

Cross-platform comparison of framed topics in Twitter and Weibo: machine learning approaches to social media text mining

Cross-platform comparison of framed topics in Twitter and Weibo: machine learning approaches to social media text mining

Remote Usability Assessment of Topic Visualization Interfaces with Public Participation Data: A Case Study

Twitmo: A Twitter Data Topic Modeling and Visualization Package for R

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