Update summaries-kalezic.md

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 In our course on machine learning and historical media, we explored how the Impresso project links data, people, disciplines, etc. to study old newspapers. We learned that newspapers are rich source of information, reflecting the ideas and beliefs of past societies. In the newspaper, we can get an idea of what people wore, how they sold food, and how they lived. These newspapers have been digitized, and we can now use machines to search through them easily. During the demo, we used the Impresso website to find out how often certain words appeared in historical newspapers. For example, we searched for words like "Atomkraft" and "nucléaire," and we saw how often they were mentioned in different countries over time. We also learned about "tokens" which are small units like words, used for counting how often something appears in the data. At the end, we did a hands-on activity in groups. My group, Group 3, worked on an Ngrams project. We searched for the term “Plan Marshall” and found it in over 68,000 mentions in 43,617 articles, with most appearing between 1948 and 1951. We discovered that language filters only worked with single tokens like "Marshall." Overall, what I took away from this course is that the group project helped us learn how to use machine learning to find patterns in historical newspapers and better understand how information was shared in the past. Finally, we learned how to use Github to submit our homework. This project helped us see how machine learning can uncover patterns in history through old newspapers. 
 
-## Summary Session 4, 16 October 2024
+## Summary Session 5, 16 October 2024
 
 In our fifth course session, we began by covering the use of maps and GIS as tools for communication and historical analysis. Then, each group had to do a hands-on activity, exploring different sites with maps and, after exploring, creating a story map about the information each group gathered. My group worked with Atlascine maps, and we chose the “Bubbe's Life Story Interview” as a way to see how the map could enhance storytelling. Later, we also created our own story map about Atlascine. In our story map, we used basic tools. We focused on answering our four questions about Atlascine using simple text and pictures. For the pictures, we took screenshots of the Atlascine website to give a visual illustration of our work. We didn’t use other tools because we were short on time due to technical problems with a demo video that didn’t work. However, we still gained certain knowledge about the story maps platform that we could use later. I personally liked the program. It’s a mix of Word documents and PowerPoint presentations, but better, with a lot of tools. Most importantly, we can customize the tools as we want and design our own map choreography with audio. For comparison, I looked at another group's work on the “John Snow Map.” They used very interesting tools in their story map, like an image of the original John Snow map. As you scrolled down their text, you could first see the recorded deaths, then the location of water pumps would appear, and further down, the contamination hotspot on the map was revealed. This group created an amazing logical structure.
 
 To answer the question of what I gained from this course, it is certainly an amazing online tool that I can and will use later for my own projects. This tool is an amazing way of showing a historical event by using maps as a historical source.
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+## Summary Session 6, 23 October 2024
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+In the six session of the course, we explored the fundamentals of social network analysis through the practical example of a wedding guest list. This exercise introduced us to mapping social relationships by identifying connections among family members and friends, helping us understand social structures in a simple, visual way. We identified individuals as "nodes," representing people connected through various social ties, and used "attributes" like age, hobbies, or relationships to guide seating arrangements and determine connections within tables. We examined the roles of "breakers" in social networks. Brokers connect different groups by passing information between them, while breakers control the flow of information, deciding whether to spread or stop it. The course taught us about two main types of networks “affiliation networks” where things stay still and “interaction networks” where things are always moving. We also learned that networks can have one type of connection and that’s named “Unipartite” or two types “Bipartite” based on what’s being linked together. Additionally, we reviewed the importance of network visualization for orientation and categorization, understanding aspects like diameter, density, and betweenness centrality. At the end, we did a hands-on activity in groups. we used Palladio, a digital tool for visualizing and analyzing data, to create and analyze our networks. My group applied the wedding example, experimenting with various attributes and connections to see how they affect the overall network structure. 
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+This course taught me how Social Network Analysis clarifies complex social systems and I especially enjoyed the hands-on activity with Palladio, which deepened my understanding of network visualization.
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