I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

I was fortunate to give a session about research in the age of the real-time Web yesterday at the College of Charleston’s Addlestone Library as part of the library’s LITE series of technology seminars. Here are my notes from yesterday’s session, with links to other goodies as well.

• Twitter’s built-in trends are primarily useful for identifying big news gathering a lot of reaction, but not necessarily too much else (especially with the prevalence of spam topics). Tools like Collecta surface trends more intelligently and, in the case of Collecta, provide a broader look at the Web beyond Twitter. Collecta brings in photos, blog posts, comments on blog posts, videos, and articles from mainstream media, giving a more complete picture of a news story or event.
• Apps like Twitter Sentiment provide a visual way to take the temperature of the Tweeting populace’s thoughts on a topic. Using sentiment analysis tools to check favorability/unfavorability of a topic or person periodically over time can make for some fairly interesting analysis.
• Wordle is a cool way to identify popular keywords in a document. As part of the LocalTweetStats project last winter, Wordle was used to flesh out top keywords, top hashtags, and the most talked-about users in a large sample of tweets by people in the Charleston metro during January and February 2009. Visualizations like this (also see Tweetcloud) make it very quick to scan large amounts of data and make them easily digestible.
• Text mining tools like Termine are great for seeking needles in haystacks of large documents. This particular tool also can do some cross-referencing with libraries of academic journals. Text mining is expanding and increasingly important in a world where datasets are growing exponentially.

These notes will be cross-posted to the LITE blog on the College of Charleston site. Many thanks to Jolanda-Pieta van Arnhem for her help and the opportunity to give a little back to my alma mater!

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