Google Search and Hot News: Sensitivity and Relevance
November 10, 2017
I read “Google Is Surfacing Texas Shooter Misinformation in Search Results — Thanks Also to Twitter.” What struck me about the article was the headline; specifically, the implication for me was that Google was not responding to user queries. Google is actively “surfacing” or fetching and displaying information about the event. Twitter is also involved. I don’t think of Twitter as much more than a party line. One can look up keywords or see a stream of content containing a keyword or a, to use Twitter speak, “hash tags.”
The write up explains:
Users of Google’s search engine who conduct internet searches for queries such as “who is Devin Patrick Kelley?” — or just do a simple search for his name — can be exposed to tweets claiming the shooter was a Muslim convert; or a member of Antifa; or a Democrat supporter…
I think I understand. A user inputs a term and Google’s system matches the user’s query to the content in the Google index. Google maintains many indexes, despite its assertion that it is a “universal search engine.” One has to search across different Google services and their indexes to build up a mosaic of what Google has indexed about a topic; for example, blogs, news, the general index, maps, finance, etc.
Developing a composite view of what Google has indexed takes time and patience. The results may vary depending on whether the user is logged in, searching from a particular geographic location, or has enabled or disabled certain behind the scenes functions for the Google system.
The write up contains this statement:
Safe to say, the algorithmic architecture that underpins so much of the content internet users are exposed to via tech giants’ mega platforms continues to enable lies to run far faster than truth online by favoring flaming nonsense (and/or flagrant calumny) over more robustly sourced information.
From my point of view, the ability to figure out what influences Google’s search results requires significant effort, numerous test queries, and recognition that Google search now balances on two pogo sticks. Once “pogo stick” is blunt force keyword search. When content is indexed, terms are plucked from source documents. The system may or may not assign additional index terms to the document; for example, geographic or time stamps.
The other “pogo stick” is discovery and assignment of metadata. I have explained some of the optional tags which Google may or may not include when processing a content object; for example, see the work of Dr. Alon Halevy and Dr. Ramanathan Guha.
But Google, like other smart content processing today, has a certain sensitivity. This means that streams of content processed may contain certain keywords.
When “news” takes place, the flood of content allows smart indexing systems to identify a “hot topic.” The test queries we ran for my monographs “The Google Legacy” and “Google Version 2.0” suggest that Google is sensitive to certain “triggers” in content. Feedback can be useful; it can also cause smart software to wobble a bit.
T shirts are easy; search is hard.
I believe that the challenge Google faces is similar to the problem Bing and Yandex are exploring as well; that is, certain numerical recipes can over react to certain inputs. These over reactions may increase the difficulty of determining what content object is “correct,” “factual,” or “verifiable.”
Expecting a free search system, regardless of its owner, to know what’s true and what’s false is understandable. In my opinion, making this type of determination with today’s technology, system limitations, and content analysis methods is impossible.
In short, the burden of figuring out what’s right and what’s not correct falls on the user, not exclusively on the search engine. Users, on the other hand, may not want the “objective” reality. Search vendors want traffic and want to generate revenue. Algorithms want nothing.
Mix these three elements and one takes a step closer to understanding that search and retrieval is not the slam dunk some folks would have me believe. In fact, the sensitivity of content processing systems to comparatively small inputs requires more discussion. Perhaps that type of information will come out of discussions about how best to deal with fake news and related topics in the context of today’s information retrieval environment.
Free search? Think about that too.
Stephen E Arnold, November 10, 2017
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Hello, Reef! The peak fall foliage season in Seoul usually around early November and, this year, the fall foliage in Seoul is expected to seen until November 20. But please keep in mind that the intensity and duration of peak fall foliage can vary depending on weather conditions! ?
September 19th. So much good stuff coming out, folks. xx