New subject: Finding what is said about a topic in other articles

14 Jun 2017


      Is there a tool already (or "how hard would it be?") which would show the
user what is said about article X in other articles. It seems to me that
there are a lot of easy content additions that might be found that way and
used to flesh out stubs and other shorter articles. What is motivating this
is because I often find that  "what links here" often points to some
surprising articles which can reveal new insights into a topic. I often
write about places. Often I think "oh, this one's nothing special" and
suddenly "what links here" reveals some interesting events that occurred
there. Discovery of a famous fossil or a big role in World War II or the
birthplace of someone quite famous. So I am wondering if there is a way to
automate this process a bit by quickly drilling down to the relevant chunk
of the article content rather than having to read/search the whole thing.
That is, if I was writing the article [[Bang Bang Jump Up]], I would want a
list along the lines of:
*        From article [[Winston Churchill]] within section "After the Second
World War" : On 23 July 1944 at [[Bang Bang Jump Up]], he met [[Harry
Truman]] to discuss the establishment of the [[United Nations]].
(False news alert: These world leaders did not meet at Bang Bang Jump Up,
but let's pretend they did.)
That is, a list of the articles with the sentence/para containing the link
or +/- N chars before or after the link, whatever's feasible to create an
intelligible snippet without having to read the whole article.
I am assuming here that article X is linked from Y (I'm not considering text
mentions). Of course, the success of the tool is its ability to pick what
might be most relevant. Nobody wants to wade through a list of irrelevant
mentions. So I would want to stick to links occurring in the prose of the
article body rather than navbox transclusions, links in citations, templates
and so forth. I also think that ordering the list by some "likely to be most
useful" metric would be beneficial (or ideally the ability of the user to
fiddle with those choices at run-time). Now until one has such a tool to get
experience with, it's hard to know what might constitute more "relevant".
But some metrics might be:
*        The relative importance of the topics. I suspect if a more
important topic is mentioning a less important topic, it might be more
relevant. Winston Churchill is more important than Bang Bang Jump Up.
*        The relative quality of the articles. I suspect if a high quality
article is mentioning a low quality article, it might be more relevant.
Winston Church is a higher quality article than Bang Bang Jump Up.
*        Being tagged by the same WikiProject (or not within the same
WikiProject). Not sure which would likely be more relevant but it might be
interesting to explore. It's unlikely Winston Churchill and Bang Bang Jump
Up are in the same WikiProject.
*        The other article is not already linked in this article. That is,
if Bang Bang Jump Up already links to Winston Churchill, then probably this
is less likely to be "new information" for the Bang Bang Jump Up article.
Anyhow, do we have a tool that does something along these lines? If not, is
there a student project here? :)
Kerry