2_use_case_name: App feedback model for NLP tasks
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: VHA: Veterans Health Administration
8_topic_area: Health & Medical
10_commercial_ai: None of the above.
11_purpose_benefits: Functional Overview: The objective is to utilize Natural Language Processing (NLP) with comment reviews for App feedback, specifically to identify named entities (NER), profanity, and stop words, and provide an automated approach to pre-processing and cleaning text for downstream analytics tools.
 
System Overview: The system uses spaCy's en_core_web_sm model, an open-source software and model, to analyze text reviews from various sources, including external sources (Google and Apple stores) and internal sources (FeedbackUI and VA Mobile). The model provides an out-of-the-box approach for NLP tasks, including NER, profanity detection, and stop word removal.
 
Data: The data sources include:
 
Text reviews from the VA's mobile applications on the Google and Apple stores (external sources)

Reviews from FeedbackUI (internal source, available in the OIA_MobileHealth database)

Reviews from VA Mobile (internal source, available via CSV files on the Mobile VA's internal website)

Users: The users of this system are likely the OCC Data Science Team, who are responsible for developing and maintaining the pipeline.
 
Target Audience: The target audience mobile application developers and other internal stakeholders who may be interested in analyzing and understanding the sentiment and feedback from these reviews.
 
12_outputs: The objective is to utilize Natural Language Processing (NLP) with comment reviews for App feedback, specifically to identify named entities (NER), profanity, and stop words, and provide an automated approach to pre-processing and cleaning text for downstream analytics tools.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 12/1/2022
19_date_acq_dev_began: 2/1/2024
20_date_implemented: 4/26/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: Unable to identify in time, working with Contracting team to identify. Iron Bow (Prime) - InnoVet (Sub)
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
33_agency_data: CDW -VA application feedback data (Ex. Share My Health Data - application download count, user review)
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
35_demo_features: Other
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: SDP / HDAP - working with contract team to better identify system nomenclature this falls under
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: No documentation is available: No documentation detailing model performance metrics, model architecture, features and intended use of the models have been created or are currently accessible to other data science teams within the agency.