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<rss xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:podcast="https://podcastindex.org/namespace/1.0" xmlns:media="http://search.yahoo.com/mrss/" version="2.0"><channel><title>Election Data Networks</title><link>https://www.spreaker.com/podcast/election-data-networks--7080080</link><description><![CDATA[This podcast explores how graph database and advance analytics can uncover patterns within election - related conversations across social media platforms. ]]></description><atom:link href="https://www.spreaker.com/show/7080080/episodes/feed" rel="self" type="application/rss+xml"/><language>en</language><category>Technology</category><copyright>Copyright Terrence C</copyright><image><url>https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg</url><title>Election Data Networks</title><link>https://www.spreaker.com/podcast/election-data-networks--7080080</link></image><lastBuildDate>Tue, 23 Jun 2026 09:56:51 +0000</lastBuildDate><itunes:author>Terrence C</itunes:author><itunes:owner><itunes:name>Terrence C</itunes:name><itunes:email>dagr1nch718@gmail.com</itunes:email></itunes:owner><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:subtitle>This podcast explores how graph database and advance analytics can uncover patterns within election - related conversations across social media platforms. </itunes:subtitle><itunes:summary><![CDATA[This podcast explores how graph database and advance analytics can uncover patterns within election - related conversations across social media platforms. ]]></itunes:summary><itunes:category text="Technology"/><itunes:explicit>false</itunes:explicit><podcast:txt purpose="ai-content">true</podcast:txt><itunes:type>episodic</itunes:type><item><title>Efficient Graph Data Loading</title><link>https://www.spreaker.com/episode/efficient-graph-data-loading--72367548</link><description><![CDATA[This podcast explores best practices for efficiently loading data into Neo4j using ETL and ELT pipelines. It discusses data transformation strategies, ingestion performance, data modeling alignment, and techniques for ensuring accuracy and scalability during large-scale imports. Perfect for data engineers, backend developers, and architects working with graph data pipelines and enterprise integrations.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72367548</guid><pubDate>Sat, 20 May 2023 13:45:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72367548/026_neo4j_data_loading_etl_elt_best_practices_nodes2022_anthony_krinsky_5v8ewzhw6_u.mp3" length="38926791" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/aad7a1e9-c0b7-4c05-9d05-d8fcf0f1b54e/aad7a1e9-c0b7-4c05-9d05-d8fcf0f1b54e.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/aad7a1e9-c0b7-4c05-9d05-d8fcf0f1b54e/aad7a1e9-c0b7-4c05-9d05-d8fcf0f1b54e.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/aad7a1e9-c0b7-4c05-9d05-d8fcf0f1b54e/aad7a1e9-c0b7-4c05-9d05-d8fcf0f1b54e.vtt" type="text/vtt" language="en"/><itunes:author>Terrence C</itunes:author><itunes:subtitle>This podcast explores best practices for efficiently loading data into Neo4j using ETL and ELT pipelines. It discusses data transformation strategies, ingestion performance, data modeling alignment, and techniques for ensuring accuracy and scalability...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores best practices for efficiently loading data into Neo4j using ETL and ELT pipelines. It discusses data transformation strategies, ingestion performance, data modeling alignment, and techniques for ensuring accuracy and scalability during large-scale imports. Perfect for data engineers, backend developers, and architects working with graph data pipelines and enterprise integrations.]]></itunes:summary><itunes:duration>2433</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>The Science of Election Analytics</title><link>https://www.spreaker.com/episode/the-science-of-election-analytics--72317983</link><description><![CDATA[Elections are more than votes; they are complex systems of data and interpretation. This episode dives into how analysts use statistics, technology, and modeling to understand electoral results. Learn how data transforms raw votes into meaningful insights about society.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72317983</guid><pubDate>Mon, 10 Apr 2023 16:25:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72317983/elections_as_a_societal_blood_test.mp3" length="16731043" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/3e1bc8d3-4180-413f-84ca-94284f0c65b4/3e1bc8d3-4180-413f-84ca-94284f0c65b4.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/3e1bc8d3-4180-413f-84ca-94284f0c65b4/3e1bc8d3-4180-413f-84ca-94284f0c65b4.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/3e1bc8d3-4180-413f-84ca-94284f0c65b4/3e1bc8d3-4180-413f-84ca-94284f0c65b4.vtt" type="text/vtt" language="en"/><itunes:author>Terrence C</itunes:author><itunes:subtitle>Elections are more than votes; they are complex systems of data and interpretation. This episode dives into how analysts use statistics, technology, and modeling to understand electoral results. Learn how data transforms raw votes into meaningful...</itunes:subtitle><itunes:summary><![CDATA[Elections are more than votes; they are complex systems of data and interpretation. This episode dives into how analysts use statistics, technology, and modeling to understand electoral results. Learn how data transforms raw votes into meaningful insights about society.]]></itunes:summary><itunes:duration>1046</itunes:duration><itunes:keywords>technology</itunes:keywords><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Seeing with Graphs</title><link>https://www.spreaker.com/episode/seeing-with-graphs--72367549</link><description><![CDATA[This podcast explores how graph data science techniques can enhance computer vision tasks by modeling relationships between visual features. It discusses graph-based representations of images and video, object relationship mapping, and how GNNs improve recognition, segmentation, and scene understanding. Perfect for AI researchers, computer vision engineers, and data scientists working at the intersection of vision and graph analytics.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72367549</guid><pubDate>Sun, 17 Apr 2022 22:31:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72367549/029_graph_data_science_for_computer_vision_nodes2022_anuj_agrawal_4lw2qbwzlri.mp3" length="38926781" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/fd6ee2c6-048c-450e-87c2-d57f92994f40/fd6ee2c6-048c-450e-87c2-d57f92994f40.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/fd6ee2c6-048c-450e-87c2-d57f92994f40/fd6ee2c6-048c-450e-87c2-d57f92994f40.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/fd6ee2c6-048c-450e-87c2-d57f92994f40/fd6ee2c6-048c-450e-87c2-d57f92994f40.vtt" type="text/vtt" language="en"/><itunes:author>Terrence C</itunes:author><itunes:subtitle>This podcast explores how graph data science techniques can enhance computer vision tasks by modeling relationships between visual features. It discusses graph-based representations of images and video, object relationship mapping, and how GNNs...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how graph data science techniques can enhance computer vision tasks by modeling relationships between visual features. It discusses graph-based representations of images and video, object relationship mapping, and how GNNs improve recognition, segmentation, and scene understanding. Perfect for AI researchers, computer vision engineers, and data scientists working at the intersection of vision and graph analytics.]]></itunes:summary><itunes:duration>2433</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Connecting Data to Reveal Patterns</title><link>https://www.spreaker.com/episode/connecting-data-to-reveal-patterns--72367547</link><description><![CDATA[This podcast explores how connecting and analyzing Google Sheets data can reveal hidden patterns, relationships, and insights that are not immediately visible in raw tables. It discusses data linking, lightweight graph thinking, pattern detection, and practical ways to improve decision-making using simple but powerful spreadsheet integrations. Perfect for analysts, business users, and productivity enthusiasts who want to unlock deeper value from everyday data tools.<br /><br />This episode includes AI-generated content.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72367547</guid><pubDate>Thu, 24 Mar 2022 13:28:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72367547/027_discover_invisible_patterns_in_your_data_connect_google_sheets_tables_and_neo4j_nodes2022_dmleuwokh6o.mp3" length="38926807" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/f7bcde61-e07a-4d03-abde-a5d5d7fc62e4/f7bcde61-e07a-4d03-abde-a5d5d7fc62e4.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/f7bcde61-e07a-4d03-abde-a5d5d7fc62e4/f7bcde61-e07a-4d03-abde-a5d5d7fc62e4.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/f7bcde61-e07a-4d03-abde-a5d5d7fc62e4/f7bcde61-e07a-4d03-abde-a5d5d7fc62e4.vtt" type="text/vtt" language="en"/><podcast:txt purpose="ai-content">true</podcast:txt><itunes:author>Terrence C</itunes:author><itunes:subtitle>This podcast explores how connecting and analyzing Google Sheets data can reveal hidden patterns, relationships, and insights that are not immediately visible in raw tables. It discusses data linking, lightweight graph thinking, pattern detection, and...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how connecting and analyzing Google Sheets data can reveal hidden patterns, relationships, and insights that are not immediately visible in raw tables. It discusses data linking, lightweight graph thinking, pattern detection, and practical ways to improve decision-making using simple but powerful spreadsheet integrations. Perfect for analysts, business users, and productivity enthusiasts who want to unlock deeper value from everyday data tools.<br /><br />This episode includes AI-generated content.]]></itunes:summary><itunes:duration>2433</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Modern Democracy as a Geometric Network</title><link>https://www.spreaker.com/episode/modern-democracy-as-a-geometric-network--72317982</link><description><![CDATA[The provided text introduces an episode titled "The Geometry of Votes: Mapping Modern Democracy," which examines the intersection of quantitative data and political processes. It focuses on the methodologies used to gather and evaluate electoral statistics to uncover hidden shifts in voter habits.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72317982</guid><pubDate>Fri, 01 Oct 2021 05:50:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72317982/modern_democracy_as_a_geometric_network.mp3" length="18995128" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/0734fcd4-8ace-4446-b513-6fc577deb75d/0734fcd4-8ace-4446-b513-6fc577deb75d.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/0734fcd4-8ace-4446-b513-6fc577deb75d/0734fcd4-8ace-4446-b513-6fc577deb75d.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/0734fcd4-8ace-4446-b513-6fc577deb75d/0734fcd4-8ace-4446-b513-6fc577deb75d.vtt" type="text/vtt" language="en"/><itunes:author>Terrence C</itunes:author><itunes:subtitle>The provided text introduces an episode titled "The Geometry of Votes: Mapping Modern Democracy," which examines the intersection of quantitative data and political processes. It focuses on the methodologies used to gather and evaluate electoral...</itunes:subtitle><itunes:summary><![CDATA[The provided text introduces an episode titled "The Geometry of Votes: Mapping Modern Democracy," which examines the intersection of quantitative data and political processes. It focuses on the methodologies used to gather and evaluate electoral statistics to uncover hidden shifts in voter habits.]]></itunes:summary><itunes:duration>1188</itunes:duration><itunes:keywords>technology</itunes:keywords><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Spring Cloud Function on Azure Explained</title><link>https://www.spreaker.com/episode/spring-cloud-function-on-azure-explained--72367550</link><description><![CDATA[This podcast explores how Spring Cloud Function integrates with Azure Functions to build flexible, event-driven, serverless applications. It discusses function-based architecture, deployment strategies, cloud portability, and how to achieve a powerful “trifecta” of Spring, serverless, and cloud scalability. Perfect for backend developers, cloud engineers, and architects looking to modernize applications with serverless patterns.]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72367550</guid><pubDate>Fri, 05 Jun 2020 14:45:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72367550/028_let_s_get_functional_pull_off_a_trifecta_with_spring_cloud_function_azure_function_nodes2022_0dhtxrcpqro.mp3" length="38926812" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/d95b2b24-cc53-4b07-b821-ba26855911ca/d95b2b24-cc53-4b07-b821-ba26855911ca.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/d95b2b24-cc53-4b07-b821-ba26855911ca/d95b2b24-cc53-4b07-b821-ba26855911ca.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/d95b2b24-cc53-4b07-b821-ba26855911ca/d95b2b24-cc53-4b07-b821-ba26855911ca.vtt" type="text/vtt" language="en"/><itunes:author>Terrence C</itunes:author><itunes:subtitle>This podcast explores how Spring Cloud Function integrates with Azure Functions to build flexible, event-driven, serverless applications. It discusses function-based architecture, deployment strategies, cloud portability, and how to achieve a powerful...</itunes:subtitle><itunes:summary><![CDATA[This podcast explores how Spring Cloud Function integrates with Azure Functions to build flexible, event-driven, serverless applications. It discusses function-based architecture, deployment strategies, cloud portability, and how to achieve a powerful “trifecta” of Spring, serverless, and cloud scalability. Perfect for backend developers, cloud engineers, and architects looking to modernize applications with serverless patterns.]]></itunes:summary><itunes:duration>2433</itunes:duration><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item><item><title>Digital Democracy</title><link>https://www.spreaker.com/episode/digital-democracy--72317981</link><description><![CDATA[Technology is rapidly changing how election information is gathered and shared. In this episode, we discuss the rise of digital platforms, real-time reporting, and interconnected data systems in modern elections. Explore how innovation is reshaping transparency and access in democratic processes.<br /><br /><br /><br /><br /><br /><br /><br /><br /><br />]]></description><guid isPermaLink="false">https://api.spreaker.com/episode/72317981</guid><pubDate>Mon, 10 Feb 2020 03:20:00 +0000</pubDate><enclosure url="https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/72317981/the_shift_to_digital_election_networks.mp3" length="15727941" type="audio/mpeg"/><podcast:transcript url="https://transcription.spreaker.com/starship/92a5d1bd-4322-4670-aef4-c6bf2b80c649/92a5d1bd-4322-4670-aef4-c6bf2b80c649.srt" type="application/x-subrip" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/92a5d1bd-4322-4670-aef4-c6bf2b80c649/92a5d1bd-4322-4670-aef4-c6bf2b80c649.txt" type="text/plain" language="en"/><podcast:transcript url="https://transcription.spreaker.com/starship/92a5d1bd-4322-4670-aef4-c6bf2b80c649/92a5d1bd-4322-4670-aef4-c6bf2b80c649.vtt" type="text/vtt" language="en"/><itunes:author>Terrence C</itunes:author><itunes:subtitle>Technology is rapidly changing how election information is gathered and shared. In this episode, we discuss the rise of digital platforms, real-time reporting, and interconnected data systems in modern elections. Explore how innovation is reshaping...</itunes:subtitle><itunes:summary><![CDATA[Technology is rapidly changing how election information is gathered and shared. In this episode, we discuss the rise of digital platforms, real-time reporting, and interconnected data systems in modern elections. Explore how innovation is reshaping transparency and access in democratic processes.<br /><br /><br /><br /><br /><br /><br /><br /><br /><br />]]></itunes:summary><itunes:duration>983</itunes:duration><itunes:keywords>technology</itunes:keywords><itunes:explicit>false</itunes:explicit><itunes:image href="https://d3wo5wojvuv7l.cloudfront.net/images.spreaker.com/nuvolari-assets/green_square_mic.jpg"/><itunes:episodeType>full</itunes:episodeType></item></channel></rss>
