Portuguese Topic Model

English Portuguese Spanish

The Topic Overview tab contains a visual representation of the topic model used for this study. A topic model is a statistical model that uses machine learning to determine the probability of correspondence between specified topics in a collection of documents. The model generates these topics on the basis of word co-occurrence. After running the model, we categorized topics into four categories: general research topics (using NSF categories), specific subfield topics, water budget topics, and method topics. These topics allow us to interpret which fields of water science have the most and the least comprehensive research—or in other words, which are the “bright” and “blind” spots of water science in Latin America.

Important note: the Spanish and Portuguese topic models rely on far smaller corpora than the English topic model. Because of this, the other two models are not as comprehensive; other visualizations on the platform thus rely on the topics generated from the English corpus.

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Topic Model: How-To

This text provides instructions for analyzing the topic model to interpret the intertopic distance and top 30 most relevant terms of each topic. Refer to the page FAQs for more tips on interpreting the information and reasoning behind the model.

1. The left panel projects the relative distance between each topic and the predicted frequency the term will appear in relevant topics. The right panel depicts the corpus-wide (blue) and topic-specific frequency (red) of each word.
2. Determine topic numbers relevant to your query using the Topic Labels at the bottom of the page.
3. Enter corresponding numbers into the Selected Topic search bar to display the Top-30 Most Salient Terms for each topic.
4. Hover over a specific word in the term list to view the predicted frequency it will appear in relevant topics.
5. To reset the model visualization, select Clear Topic

FAQ Page

Topic Overview

Topic Labels

This searchable table contains labeling information for individual topics in the model. Each topic label corresponds to a specific topic shown above. Irrelevant topics (“noise”) are unlabeled. In the Spanish and Portuguese Topic Labels, there is a column representing the corresponding topic found in the English model. We include this data because we based the rest of our study off the English model due to the lack of data within the Spanish and Portuguese corpora. This is also noted in the Topic Model description.

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Topic Labels: How-To

To use this table, follow these steps:

1. Click on Search Options to apply filters to the table or use the search bar on the right to narrow down the number of topics. To order the rows alphabetically or numerically, click on the arrows next to each table header.
2. Click Download CSV or Download Excel to download the table as a comma-separated value or Excel file, respectively. Users can also click on specific rows to highlight them and download just those rows.
3. For more information on the articles used in the model, check the Document to Topic tab above.

Topic Number	Topic Label	NSF Specific	NSF General	Description	Topic in English Model
Topic Number	Topic Label	NSF Specific	NSF General	Description	Topic in English Model

Article Listings

This searchable table contains information about the articles used in the model. With it, users can construct queries to find information about authors, publishers, and, in some cases, specific geographic features or areas. Irrelevant topics (“noise”) are unlabeled. We include this article listing as a supplemental resource, which lacks some data fields for the English corpus; this is because there were not enough articles available in Spanish and Portuguese to accurately identify the total amount and type of topic labels. This means all labels were derived from the English corpus.

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Article Listings: How-To

The table lists all the articles that make up the corpus and any relevant information including the author(s), title, year, source, DOI (digital object identifier), predicted country, top topic, and topic label. To use the table, follow these steps:

1. Click on Search Options to apply specific filters to the table or use the search bar to narrow down the number of papers.
2. To increase the number of rows in the table, click on the Show 10 Rows button and change the number of rows.
3. To order the rows alphabetically or numerically, click on the arrows next to each table header.
4. Click Download CSV or Download Excel to download the table as a comma-separated value or Excel file, respectively. Users can also click on specific rows to highlight them and download just those rows.

Author(s)	Title	Year	Source	DOI	URL
Author(s)	Title	Year	Source	DOI	URL