1. http://tiny.cc/PresentationACP
2. How the project looks now
2.1. CRISJ
2.1.1. https://crisj.org/race-news-and-research-curation-project
2.2. CHLFSA
2.2.1. https://crisj.org/chlfsa-news-news-and-research-curation-project
3. News Media in 2023
3.1. About 3 decades since the public release of the Internet
3.1.1. Web 1.0
3.1.1.1. Convergence
3.1.2. Web 2.0
3.1.2.1. Mass social interaction
3.1.3. Web 3.0
3.1.3.1. Semantic
3.2. How it looks for many people
3.2.1. Show Bing News Navigation Screen
3.2.2. Show Bing News "Personalization" screen
3.2.3. Individual exposure to content
3.2.3.1. Narrowcasting
4. Knowledge Graphs
4.1. What are they?
4.1.1. Pre-processed information
4.1.2. A knowledge graph is like a big, interactive mind map that stores and organizes information about different topics. Imagine a large web, with each point on the web representing a piece of information or an idea. These points, called nodes, are connected by lines, called edges, that show how the pieces of information are related to each other. For example, in a knowledge graph about animals, there could be a node for 'lion,' a node for 'mammal,' and a node for 'Africa.' The edges between these nodes would show that a lion is a mammal and that lions live in Africa. This way, the knowledge graph helps us understand how different ideas are linked and can make it easier to find specific information or discover new connections between topics.
4.2. The nodes are considered semantic
4.2.1. Nodes in a knowledge graph are considered semantic because they represent concepts or entities in a way that captures their meaning and relationships with other concepts. Semantic refers to the study of meaning in language and communication, and when applied to nodes, it implies that they carry meaning beyond just a simple data point or keyword. In a knowledge graph, nodes are not just isolated pieces of information; they are part of a structured and interconnected network that helps computers and humans better understand the context and relationships between different concepts. By organizing information semantically, knowledge graphs enable more efficient and accurate retrieval, analysis, and interpretation of data. For example, if a node represents the concept "car," it might be linked to other nodes representing "vehicle," "transportation," and "engine," creating a semantic understanding of what a car is and how it is related to other concepts. This semantic structure helps both humans and computers make sense of the information in the knowledge graph and allows for more intelligent and relevant processing of queries or analysis.
4.3. The edges or connections are considered semantic
4.3.1. Edges in a knowledge graph are considered semantic because they represent meaningful relationships between the nodes (concepts or entities) they connect. These relationships go beyond simple associations and help convey the context and meaning of the connection between two nodes. In a knowledge graph, edges often have labels that describe the type of relationship between the connected nodes, making it clear how the concepts are related. By providing this additional layer of meaning, semantic edges enable a more accurate understanding of the connections between different pieces of information. For example, consider a knowledge graph with nodes for "Albert Einstein," "physics," and "Germany." The edges connecting these nodes could be labeled as "is a scientist in," "was born in," and "is a field of study in," respectively. These semantic edges help to clarify the specific relationships between the nodes, allowing for better interpretation of the data and improved query processing. In summary, edges in a knowledge graph are considered semantic because they represent meaningful relationships between nodes, going beyond simple connections and providing context and meaning that help both humans and computers better understand the structure and content of the graph.
4.4. Types of entities
4.4.1. Article
4.4.1.1. News articles
4.4.2. Organization
4.4.3. Person
4.4.4. Place
4.4.5. Product
4.4.6. Job
4.4.7. Image
4.4.8. Video
5. Articles
5.1. Articles
5.1.1. author authorUrl breadcrumb categories date discussion estimatedDate html icon images language nextPage nextPages numPages publisherCountry publisherRegion quotes sentiment siteName tags text title videos
5.2. Entities metadata generated by 2 methods
5.2.1. Information extracted from the article
5.2.2. Information generated from the article
5.2.2.1. categories tags sentiment
5.3. Demonstration
5.3.1. DIFFBOT
5.3.1.1. https://www.diffbot.com/
5.3.1.1.1. https://app.diffbot.com/search/
5.3.1.2. MIT Technology Review
5.3.1.2.1. https://www.technologyreview.com/2020/09/04/1008156/knowledge-graph-ai-reads-web-machine-learning-natural-language-processing/
5.3.2. Article searches
5.3.2.1. type:Article text:"criminal alien" text:"immigration" sortBy:date
5.3.2.2. type:Article text:"criminal alien" text:"immigration" facet:siteName
5.3.2.3. type:Article text:"criminal alien" text:"immigration" facet:sentiment
5.3.2.4. type:Article text:"criminal alien" text:"immigration" facet:tags
6. How it is implemented in CRISJ and CHLFSA
6.1. 2 different knowledge graphs
6.1.1. DIFFBOT's Web Knowledge Graph
6.1.2. SERPAPI - Very similar to Google Knowledge Graph
6.1.2.1. https://crisj.org/chlfsa-relevant-news-and-research-curation-project
6.2. Awareness
6.2.1. Ability to create news feeds on a topic pertaining CHLFSA and/or CRISJ missions
6.3. Community Building
6.3.1. Defeat narrowcasting
6.3.2. Enable conversations
6.3.2.1. Watercooler conversations
6.3.2.2. Academic conversations
6.4. Research Focus
6.4.1. Clean content for analysis
6.4.1.1. Automated analysis
6.4.1.2. A lot of information = Large scale
7. How to participate
7.1. Topics important for the community Dr. Barajas - CA Farmworkers
7.1.1. https://crisj.org/news-and-research-curation-project
7.2. Awareness and Community Building
7.2.1. CRISJ Sister organizations
7.2.2. Based on your organization's needs, what content in the news media should be captured?
7.2.2.1. Relevance to your mission
7.2.2.2. Value of the news feed for the community
7.2.3. Share the word
7.2.3.1. To visit CRISJ to check the community's news curation
7.2.4. Contribute
7.2.4.1. Think carefully about things that would be worthwhile to monitor
7.3. Research
7.3.1. Faculty and Graduate Students https://www.diffbot.com/students/