## (Baseball) Bibliometrics: Calculating the Scoreboard

This post was guest authored by Scholarly Communication and Publishing Graduate Assistant Paige Kuester. This is the second part of a three-part series. Read Part 1 here.

In our last post, we discussed what makes a journal the best team for a scholarly player (sort of). Today, we are looking at scores that are used to directly measure the impact of scholarly articles and the authors themselves.

# H-index

Now this score is a bit trickier to calculate. But first, it’s probably best to explain what it is and what it does. H-index focuses on a specific researcher’s own output, in both the form of their most cited papers and also using the number of citations of their work that others have used. Yeah, this is a curve ball.

Now if we were really going to spend an afternoon at the ballpark learning about scholarly measurements, then we would go into the nitty gritty of how to figure out the most cited papers, and also how to actually figure out an h-index. But in simple terms, you need to list the number of publications with the most citations in descending order. Next, you go down the list until the number of citations is no longer greater than or equal to its position in the list. The last citation that is greater than or equal to its position in the list is the h-index. Check out this Waterloo library guide for an example.

Otherwise, you can also just look it up. The scores might vary between websites because of the differences in their content, but Google Scholar, Web of Science, and Scopus all give an h-index.

If none of this made sense, here’s a plug for the Wikipedia page that informed my basic understanding.

There is not a metric in baseball that’s like this. Maybe if our baseball team had a starting line up where the players with the most home runs started and went down the order in descending number of home runs, but cut off when the the lineup reached the last player that had a greater or equal number of home runs as the position that they were in? There is more strategy than that to batting order, so that is clearly not how it works, but you knew coming into this that this was going to be a stretched metaphor, anyway.

So what’s next?

# G-index and i10-index

Both of these indices are not as widely used as the h-index.

The g-index is supposed to be an updated version of the h-index that places more value on highly cited articles.

i10 is only used on Google Scholar, and can be remembered by its name: it is the number of articles that an author has that have 10 citations or more each.

Okay, I think we’ve lost focus on the game, but we will come back to it in the next post.

Don’t worry, we’re in the seventh inning stretch. The game is about to get a whole lot more exciting, but I promise we won’t go into extra innings.

## (Baseball) Bibliometrics Broken Down: A Series

This post was guest authored by Scholarly Communication and Publishing Graduate Assistant Paige Kuester. This is the first part of a three-part series.

No matter what game, everyone wants to be the best. Play for the best team, have the highest score, whatever. The game of research is no different. Now, I don’t mean to suggest that research and publishing should not be taken seriously by calling it a game, but there are still high scores involved that may be the deciding factor in the end result, which could be tenure or a higher paycheck or just negotiating power. You have probably heard of some of these scores, like the h-index or altmetrics. Even if you know what they mean, you might not know their significance or how they are calculated. And if you do know all of that, your time might be better spent elsewhere, unless you enjoy a super-stretched sports metaphor.

Yes, to further extend this game metaphor, we’re going to spend an afternoon at the ballpark. I’m visualizing Wrigley, but we can go wherever your favorite team plays, as long as it’s a Major League team. I know that I might be losing you at this point, and I might get lost in this imperfect metaphor myself, but if we make it through, there’s sure to be a win at the end.

In this game, our scholarly authors (professors) are our players (professionals). This could be humorous, but don’t laugh yet, because these scholars are playing a serious game. Even though getting on the starting line up does not guarantee a spot later in the season, I am going to equate that with gaining tenure for professors, as they are both goals that take hard work and dedication to achieve.

Journal Impact Factor

In order to have a good career, being on a highly ranked team is an automatic boost. They’re usually good for a reason, and fans will think that you must be good if you started off on such a prestigious team.

Picking a journal to publish in is a similar process, at least for the sake of this argument. While journals don’t go out and recruit, they are ranked in different ways, just like baseball teams. One way is through journal impact factor, which ranks the journals based on the average number of citations that a typical article has had in the last two years.

The formula works like this: take the number of cited articles from the journal that is in question during a two year period that were indexed during the following. Next, find out how many articles there were that were published and citable during that same two-year time period. Divide the first number by the second number, and you’ve got journal impact. This is formula is actually easier than figuring out the top ranked baseball teams in terms of math, but if you are really up for a challenge, you can try that, too.

If you didn’t get that math, that’s just fine, because there are websites that do it for you. Journal Citation Reports puts out the scores every year, and, as in most sports, the higher the better.

Originally, Impact Factor was not supposed to be used to judge how good an author or an article was was, but this is one way that many judge those authors now. If you can play for a good team, if you can get your article published in a highly ranked journal, you must be good, right?

Well, not everyone thinks that this is a representative way to measure academic impact, so there are other specific measures for the players and their articles, which will be discussed in the next post. Don’t worry, we’re just getting started.