Only 2 of the tweets were actual job postings. Both of those were for the same job, located in Houston, Texas.
Also of interest, although not job postings, were:
- A retweet of @STC_Austin promoting Jack Molisani's upcoming "Job Hunting Secrets that Might Surprise You" job hunting presentation for STC Austin:
- A German web site about #techcomm job profile & tasks, w/ salary survey: http://www.beruf-technischer-redakteur.de/
Searching on #techcomm AND #jobs yielded only the 2 postings for the Houston job mentioned above.
The next thing I tried was "technical writer" AND #jobs. That one seems to be the mother lode. 500 hits! That's a bit much to analyze manually, so I tried the search using The Archivist, which not only allows you to export to an Excel spreadsheet but does some interesting visualizations on the data. I made my search archive public so I could link to it here: Archive on "technical writer" #jobs Containing 500 Tweets: http://archivist.visitmix.com/hammerchick/1
Alas, the visualizations don't include location. The data exported to Excel includes latitude and longitude of the tweet, which isn't necessarily the latitude and longitude of the job, so I'm not sure it's worth my trying to figure out how to get Excel to translate the coordinates to a map location. Instead, I read the text of each tweet and identified the ones that specified a location, entered the location in a spreadsheet, and made the bar chart shown above. The top three locations were California with 13, Maryland with 8, and North Carolina with 6. So, for today, where the tech writer job tweets are is California.
I need to work on automating the location data. This is a work in progress.