Summary
The article “Visualizing Email Content: Portraying Relationships from Conversational Histories” is about Themail, a visualization that shows how people correspond to each other and how their relationship changes over time. It explains the parsing approach and interface, and further implications for research related to email content visualization. According to the article, users store a vast amount of emails ranging from insignificant to important. While many of these emails are insignificant, the pattern of emailing in which we develop becomes important. Two major themes are discussed: the appreciation of the overall picture, known as the haystack, and seeking specific pieces of information, known as the needle. Email visualizations fall into four main categories: thread based visualizations, social-network visualizations, temporal visualizations, and contact-based visualizations. Themail displays its information in yearly words and monthly words. Yearly words are used to show a broad overall tone of the relationship. This shows what people are usually conversing about, while ignoring words that are only used on special occasion. Monthly words are used to show a much more detailed portrait of past email exchanges. People were excited to look back at their email archives, and preferred looking at archives related to their family and loved ones.
Reflection
I believe that Themail is an extremely useful tool that should be used by all people that frequently email. Although I had never heard of it before, I would be very interested to interact with the tool to see the visualizations of my email archives. I think that this is something that should be more publicly broadcasted to the public, because many people do not delete their emails. People keep emails of conversations, news, and other relevant information that could be useful to analyze. It would be interesting to see this tool used on other platforms besides email. Many people have conversations on social media sites such as Facebook and Twitter, and rarely delete their messages. Seeing also how their results vary between platforms, analyzing whether or not they talk about certain topics more on specific platforms.
Questions
Are there any other visualizations out there like this?
Could this tool be incorporated into other social computing platforms?
