Topic Modeling and Visualization for Big Data in Social Sciences

Sukhija, Nitin; Tatineni, Mahidhar; Brown, Nicole M.; Moer, Mark Van; Rodriguez, Paul; Callicott, Spencer

doi:10.1109/uic-atc-scalcom-cbdcom-iop-smartworld.2016.0183

Cited by 21 publications

(11 citation statements)

References 7 publications

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“…As a case, textual visualization is a solution to improve textual analysis-in terms of speed and clarity-by providing researchers a top-down view of the topics in a corpus and identifying the relationships between topics and other attributes (e.g., political ideologies, gender, etc.). Text visualization is now used in a wide variety of domains, from communicative (Viégas, et al, 2009) to exploratory analysis of topic models (Sukhija, et al, 2016) and single document visualizations.…”

Section: Unstructured Data: Textual Datamentioning

confidence: 99%

Using Data Visualizations to Study Digital Public Spaces

Ng¹

2022

Preprint

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This article reviews the history and current data visualizations in studying digital public spaces. I will discuss the recent development of visualizing raw data numerically, relationally, spatially, and textually. Each method involves different visual representations to integrate data collection with analysis and presentation of results. Through a case study of global web use, this article also demonstrates a thinking process and analytical workflow to incorporate data visualizations when studying digital public spaces, particularly in the midst of a global crisis.

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Section: Unstructured Data: Textual Datamentioning

confidence: 99%

Using Data Visualizations to Study Digital Public Spaces

Ng¹

2022

Preprint

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“…This is a widely used approach for analyzing large text collections. In particular, Latent Dirichlet Allocation (LDA) is one of the most popular topic modelling approaches to aggregate vocabulary from a document corpus to form latent "topics" [18].…”

Section: Analyzing Data Using Topic Modelingmentioning

confidence: 99%

Corpus Analysis of Earthquake Related Tweets through Topic Modelling

Maceda¹,

Llovido²,

Palaoag³

2017

IJMLC

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The Philippine archipelago is one of the most disaster-prone area due to its location. As Twitter grows everyday, it has now become a valuable source of people's opinion. The main purpose of the study is to use Twitter, as text corpora in the attainment of disaster risk reduction. Earthquake related tweets posted from July 1, 2017 to August 31, 2017 were programmatically collected. Data cleaning was made by removing noisy words, hence, from 90,692 collected tweets this resulted to 41,500 cleaned tweets. Topic modeling identifies patterns in a corpus. Findings revealed that there is a need to strengthen the conduct of earthquake drill and early warning notices to lessen the vulnerability of people and property, and reduce the causal damages of earthquake, thus improve its community resiliency. Topic results shall be discussed with concerned agencies for its possible consideration and inclusion to enhance the earthquake-related disaster management plan.

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“…[7,8,9]. All these purposes have an important position in social science and data analysis [10,11,12].…”

Section: Background and Motivationmentioning

confidence: 99%

“…Then for all the internal tree nodes on the search paths of[5,15], we check whether there are subtrees of y axis attached to them. For these subtrees of y axis under the internal tree nodes, we query the range[3,11] of y axis. The leaf nodes of all the subtrees on the other dimensions are always falling in the range under the subtree roots in the previous dimension.…”

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confidence: 99%

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Topic Ranger : a tool for topic exploration and analysis of spatio-temporal documents

Lü¹

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Topic Modeling and Visualization for Big Data in Social Sciences

Cited by 21 publications

References 7 publications

Using Data Visualizations to Study Digital Public Spaces

Using Data Visualizations to Study Digital Public Spaces

Corpus Analysis of Earthquake Related Tweets through Topic Modelling

Topic Ranger : a tool for topic exploration and analysis of spatio-temporal documents

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