It’s been over 25 years since I wrote the Official Netscape Guide to Internet Research (and 24 years since I started my blog ResearchBuzz), but search engines and the problem of finding things on the Internet remain just as fascinating to me. Over this summer I began trying to actually solve search challenges instead of just thinking about them — and working out techniques to minimize them.
They’re all freely available at researchbuzz.github.io. Some of them require API keys, but the keys are free as well.
I love all my little Gizmos and could never pick an absolute favorite, but I think these would be most useful to journalists.
You may have seen a cute little Twitter hack — popularised by Andy Baio — which allows you to roll back the years and recreate a decade-old Twitter timeline. The twist is that you’ll be seeing updates from people who you may not have been following at the time but discovered later.
Nostalgia aside, the same technique could be used by journalists to track what was being said by any particular group of interest at a particular point in time. Here’s how. Continue reading →
Last week one of the students on my MA in Online Journalism was looking to find French people based in the city for a local angle on the presidential elections taking place in France. “Ah!” I thought. “That’s a job for a Facebook Graph search”. It’s the sort of situation that arises regularly in the newsroom — so here’s how to do it:
What is Facebook Graph search — and why is it useful for journalists?
Facebook Graph Search in 2013
Facebook Graph was launched in 2013 as a specific tool for finding people based on their interests. The ‘graph’ part refers to its ability to find people based on intersecting qualities: combinations of their likes, places of work, friends, and where they live and come from.
The tool itself was dropped in 2014, but the ability to search based on intersecting qualities remained, as part of the general Facebook search. You just have to know how to use it… Continue reading →
Here, then, are some reflections on the 10 pieces which did best in 2016 (there were 100 posts across the year), plus the older posts which keep on giving, and a comparison of some pieces which did far better on Medium than on OJB. Continue reading →
Tonight many journalists will have Tweetdeck or similar social media dashboards ‘tuned in’ to coverage of the US election, typically by creating columns to monitor activity on key hashtags like #Election2016. But on a big occasion like this, the volume of tweets becomes unmanageable. Here then are a few quick techniques to surface tweets that are likely to be most useful to reporters:
Picking the right hashtags: Hashtagify
Hashtagify is a tool for finding out the popularity of certain hashtags. Type a tag into the search box and you’ll get a network diagram like the one shown above — but you can also switch to ‘Table mode’ to get a list of tags that you can sort by popularity, correlation, weekly or monthly trend. Continue reading →
When a journalist gets their first job, or switches role to a new area or specialism, they need to quickly work out where to find useful leads. This often involves the use of feeds, email alerts, and social networks. In this post I’m going to explain a range of search techniques for finding useful sources across a range of platforms. Continue reading →
Finding Snapchat accounts to follow is harder than it needs to be. There are some directories, such as Snapcodes, but these rely on user submissions. The iPhone app GhostCodes also ‘curates’ lists of accounts by category, but also relies on users giving their own usernames.
You can find some articles highlighting interesting accounts to follow on Snapchat. One useful search phrase to use for finding those is this:
Here are 4 useful techniques for tracking them down.
Method 1: The advanced search
The most obvious approach is to look for some articles highlighting interesting accounts to follow on Snapchat. You can narrow this a little by using search operators like allintitle: (which restricts results to those where the words are in the page title).
When a national news story breaks and you need local reaction, how do you exclude the national-level updates that dominate all the other coverage? On Twitter there’s a simple answer: search within lists.