Data Mining the Twitter API for Academic Libraries
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The document discusses data mining the Twitter API. It provides an overview of how to build a URL request to submit to the Twitter API to retrieve tweets, convert the returned JSON data, insert non-duplicative tweets into a MySQL database, and then display the tweets by pulling them from the MySQL table. It also discusses potential future developments, such as developing additional keywords and notifications.
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- 1. DATA MINING THE TWITTER API 2012 ALAO Annual Conference Friday, October 26, 12
- 2. Photograph by Max Dannenbaum/Getty Images THE AGE OF BIG DATA Friday, October 26, 12
- 3. “It’s a revolution... We’re just getting under way. But the march of quantification, made possible by enormous new sources of data, will sweep through academia, business and government. There is no area that is going to be untouched.” Gary King, Director Institute for Quantitative Social Science, Harvard University Friday, October 26, 12
- 4. Wordpress posts Industrial Equipment Household Appliances Weather Instagrams Electric Meters Tweets Water Meters Government Data Traffic Tumblr posts Search Traffic Automobiles Friday, October 26, 12
- 5. Why do we want these Tweets? Vertical scroll Discover & respond to user needs proactively Create social rapport with users Build social capital Add followers Gain unique insight into Zeitgeist of user base Capture as an additional data point Friday, October 26, 12
- 6. Friday, October 26, 12
- 7. Open Source: take whatever you want, use however you want Proprietary: pay for each tool in the garage, use them as designed API: utilize the services of the garage, if you have authorization and ask the right way DATA ACCESS The Neighbor’s Garage Analogy Friday, October 26, 12
- 8. High-Level Overview Build URL request with keywords and other parameters Submit URL request Convert returned JSON data <?php ?> Insert non-duplicative data into MySQL table <?php mysql ?> Display data by pulling out of MySQL table <?php mysql html css ?> Friday, October 26, 12
- 9. <?php echo '<head>'; echo '<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />'; echo '<link rel="stylesheet" href="style.css" type="text/css" />'; echo '</head>'; echo '<body>'; mysql_connect("localhost", "user", "pass") or die(mysql_error()); mysql_select_db("database") or die(mysql_error()); $tweet_archive = mysql_query("SELECT * FROM twindicators where loc NOT LIKE '%Beach%' ORDER BY id DESC"); echo '<div class="content">'; while ($row = mysql_fetch_array($tweet_archive)) { $decoded_text = urldecode($row["text"]); echo '<p><span class="user">' . $row[user] . '</span> | <span class="date">' . $row[date] . '</span> <br /><br /> <span class="text"><a href="https://twitter.com/#!/' . $row[user] . '/status/' . $row[twid] . '">' . $decoded_text . echo '<hr />'; } echo '</div>'; echo '</body>'; ?> DISPLAY DATA BY PULLING OUT OF MYSQL TABLE Friday, October 26, 12
- 10. 70 followers NOTABLE INTERACTIONS Friday, October 26, 12
- 11. Future Developments Develop a deeper set of keywords Develop a richer interface for librarians Incorporate SMS notifications to subject specific librarians when relevent tweet is recorded Analyze data for user satisfaction / areas for improvement Friday, October 26, 12
- 12. SHAMELESS PLUG Web Service APIs and Libraries. ALA Editions Friday, October 26, 12
- 13. Jason Paul Michel micheljp@muohio.edu @jpmichel Code: Query and store: https://gist.github.com/3846007 Display: https://gist.github.com/3846055 DETAILS & SUCH Friday, October 26, 12