# SEASR: Location Entities To Google Map

> SEASR's Location Entities To Google Map is a tool for extracting locations from a text that can be displayed on a map

**Wikidata**: [Q126084539](https://www.wikidata.org/wiki/Q126084539)  
**Source**: https://4ort.xyz/entity/seasr-location-entities-to-google-map

## Summary
SEASR's Location Entities To Google Map is a software tool designed to extract geographic locations from text and display them on a map. It functions as a utility for data visualization, visual analysis, and content discovery within the digital humanities. The tool is listed in the Social Sciences and Humanities Open Marketplace and the Text Analysis Portal for Research (TAPOR).

## Key Facts
- **Classification:** Instance of software.
- **Primary Function:** Extracts location entities from text and generates a map display.
- **Key Use Cases:** Data visualization, discovery, analysis, visual analysis, and content analysis.
- **Collections:** Indexed in the Social Sciences and Humanities Open Marketplace and the Text Analysis Portal for Research (TAPOR).
- **Reference URLs:** Documented at `marketplace.sshopencloud.eu` and `tapor.ca`.
- **Language:** Documentation and resources are available in English.

## FAQs
### Q: What is the primary function of SEASR: Location Entities To Google Map?
A: The tool analyzes text to identify and extract location entities, which are then visually displayed on a Google Map interface to aid in geographic data analysis.

### Q: What specific analytical tasks is this tool used for?
A: It is utilized for data visualization, content analysis, visual analysis, and general discovery of geographic information within texts.

### Q: Where can this tool be found or accessed?
A: It is cataloged in the Social Sciences and Humanities Open Marketplace and the Text Analysis Portal for Research (TAPOR), with records available in English as of November 2022.

## Why It Matters
SEASR's Location Entities To Google Map addresses the challenge of "reading" spatial data within large volumes of unstructured text. By automating the extraction of location entities, the tool bridges the gap between textual analysis and geographic information systems (GIS). This capability is significant for researchers in the social sciences and humanities, as it allows for the "visual analysis" of literary works, historical documents, or social data, revealing patterns and connections that might be missed through reading alone.

The tool transforms abstract text into concrete "data visualization," facilitating a deeper understanding of setting and movement within a dataset. Its inclusion in major research portals like TAPOR and the SSH Open Marketplace underscores its relevance as a standard utility for digital humanists seeking to incorporate spatial reasoning into their content analysis workflows.

## Notable For
- **Text-to-Map Integration:** Uniquely combines natural language processing (entity extraction) with the visual interface of Google Maps.
- **Digital Humanities Utility:** Specifically tailored for academic and research contexts rather than general consumer navigation.
- **Multi-Modal Analysis:** Supports distinct but related functions including discovery, visual analysis, and content analysis.
- **Curated Research Tool:** Recognized and cataloged by major research aggregators like the SSH Open Marketplace.

## Body
### Functionality and Features
SEASR's Location Entities To Google Map operates as a software component designed to parse textual input. Its core mechanism involves identifying specific strings of text that denote geographic locations. Once these entities are extracted, the tool maps them onto a Google Map interface, providing an immediate visual representation of the spatial data contained within the source text.

### Applications in Research
According to the Social Sciences and Humanities Open Marketplace, the tool is classified for several high-level research applications:
*   **Data Visualization:** converting textual location data into map markers.
*   **Content Analysis:** identifying the frequency and distribution of location references in a corpus.
*   **Discovery:** uncovering geographic trends or outliers within a text.
*   **Visual Analysis:** interpreting the spatial relationships between extracted entities.

### Availability and Provenance
The tool is classified strictly as "software" (a non-tangible executable component). It is maintained within specific academic ecosystems. It is a featured tool in the **Text Analysis Portal for Research (TAPOR)** and is also listed in the **Social Sciences and Humanities Open Marketplace**.
*   **Documentation:** The tool is described at `https://tapor.ca/tools/136` and `https://marketplace.sshopencloud.eu/tool-or-service/8Mu1oy`.
*   **Metadata:** Records for this tool were last verified in English in November 2022.

## References

1. [Source](https://marketplace.sshopencloud.eu/tool-or-service/8Mu1oy)
2. [Source](https://tapor.ca/tools/136)