2_use_case_name: Social listening to inform youth programming in Colombia (previously "Communications Strategy")
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Colombia
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Youth conversations are dynamic and are defined by geographic location, socioeconomic conditions, conflicts with the law, environment, level of vulnerability, gender and ethnicity. Youth develop their voices and identity and mobilize through the media, especially social networks. Active listening methods are a fundamental element to understand their interests, role models, and relevant issues in the youth agenda, in order to design campaigns and communication strategies that are relevant, segmented, and engaging. Consequently, the Youth Resilience Activity (Programa Jovenes Resilientes #EfectoColectivo), leverages Artificial Intelligence tools developed by Audience Insights (in partnership with Twitter and Facebook), using ethical data analysis guidelines (anonymization without personal identifying information). The tool collects and analyzes findings on defined variables (e.g., location, age, followers of an @ or #, interests), allowing us to understand socio-demographic trends and general correlations with greater precision. This allows the Program to creatively develop campaigns and strategies that are highly relevant to young people and their contexts, using distribution channels that they most often consult, thereby increasing the messages’ effectiveness, relevance and engagement with youth. Using the IBM Watson platform, the Audience Insights tool provides information on audience affinity, general interest trends, media following, rankings, and personality profiles. In addition, the Insights tool for Facebook provides general data on the number of people in a specific geography or segmentation, juxtapositions (for example, which other accounts they follow) and percentages of types of devices on which they connect.
12_outputs: Reports, visualizations
16_dev_stage: Retired
17_impact_type: Neither
21_date_retired: 7/15/1905
22_dev_method: Developed with contracting resources.
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: Yes
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: Age, Other
35_question_type: Location, social media use metrics
37_custom_code: Yes
38_code_access: No – agency does not have access to source code.
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No relevant resources
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
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.