Twenty percent of Google Knowledge Graph results for trending keywords are outdated, according to a new study from SEO firm Conductor. They set out to discover whether there was a mismatch or lag distribution in Knowledge Graph entries, as compared to the corresponding Wikipedia entry.
Conductor built two lists of 50 keywords, to reflect “normal” and trending topics. They focused on people keywords to ensure some consistency across the two samples, using the Top 50 people in Google Insights and Google Trends for trending keywords, with the Top 50 on Forbes’ Celebrity 100 for the normal keywords.
1 of 5 High Activity Knowledge Graph Queries Outdated
In their analysis, Conductor found that high activity queries, such as a current search for LeBron James, are more likely to have rapidly updating Wikipedia entries and mismatched Google Knowledge Graph entries. One out of five of these high activity queries saw outdated results in the Knowledge Graph bar, compared to just 4 percent for normal queries.
Conductor explains how they came up with a lag time:
For each query we compared the Knowledge Graph result on the SERP to its Wikipedia entry and noted whether it was or was not an exact match. When they did not match, we measured the lag distribution of the mismatched queries by using WikiBlame to determine when the change occurred and, subsequently, the number of days the Knowledge Graph was behind.
Google Knowledge Graph Results - Not Quite Reliable Research
There has been many a debate over the past several years about whether Wikipedia itself can be considered a reputable, reliable source of information, especially in academia. Google’s Knowledge Graph brings these results on some topics right to the SERPs, negating the need for the user to even click through to the Wikipedia entry for basic information. Users comfortable enough referencing Wikipedia may have no problem pulling information from Knowledge Graph results.
However, the risk of finding incorrect or outdated information is compounded by the mismatch on high volume queries and the lag between updated Wikipedia entries and their corresponding Knowledge Graph entries.
Conductor notes that, “While a real time Wikipedia update may ultimately not be practical, if Google is indeed positioning Knowledge Graph as the future of search, we have to believe that they can do better than the 2-4 day lag many of their mismatched keywords currently reflect.”
In addition, users must remember they are still ultimately responsible for verifying the validity of information found on the Internet, even when it is presented on the front pages of Google.