1	Introduction to Bibliometrics Module 7 Applied Bibliometrics KAN Min-Yen
2	What is Bibliometrics? Statistical and other forms of quantitative analysis Used to discover and chart the growth patterns of information Production Use
3	Outline What is bibliometrics? √ Bibliometric laws Properties of information and its production
4	Properties of Academic Literature Growth Fragmentation Obsolescence Linkage
5	Growth Exponential rate for several centuries: “information overload” 1^st known scientific journal: ~1600 Today: LINC has about 15,000 in all libraries Factors: Ease of publication Ease of use and increased availability Known reputation
6	Zipf-Yule-Pareto Law P_n≈ 1/n^a where P_n is the frequency of occurrence of the n^th ranked item, and a is some constant. “The probability of occurrence of a value of some variable starts high and tapers off. Thus, a few values occur very often while many others occur rarely.” Pareto – for land ownership in the 1800’s Zipf – for word frequency Also known as the 80/20 rule and as Zipf-Mandelbrot Used to measure of citings per paper: # of papers cited n times is about 1/n^a of those being cited once, where a ≈ ____
7	Random processes and Zipfian behavior Some random processes can also result in Zipfian behavior: At the beginning there is one “seminal" paper. Every sequential paper makes at most ten citations (or cites all preceding papers if their number does not exceed ten). All preceding papers have an equal probability to be cited. Result: A Zipfian curve, with a≈1. What’s your conclusion?
8	Lotka’s Law The number of authors making n contributions is about 1/n^a of those making one contribution, where a ≈__ Implications: A small number of authors produce large number of papers, e.g., 10% of authors produce half of literature in a field Those who achieve success in writing papers are likely continue having it
9	Lotka’s Law in Action
10	Bradford’s Law of Scattering Journals in a field can be divided into three parts, each with about one-third of all articles: 1) a core of a few journals, 2) a second zone, with more journals, and 3) a third zone, with the bulk of journals. The number of journals is __:__:__ To think about: Why is this true?
11	Fragmentation Influenced by scientific method Information is continuous, but discretized into ________________ (e.g., conference papers, journal article, surveys, texts, Ph.D. thesis) One paper reports one experiment Scientists aim to publish in _____________
12	Fragmentation Motivation from academia The “popularity contest” Getting others to use your intellectual property and credit you with it Spread your knowledge wide across disciplines Academic yardstick for tenure (and for hiring) The more the better – __________________ The higher quality the better – ___________ To think about: what is fragmentation’s relation to the aforementioned bibliometric laws?
13	Obsolescence Literature gets outdated fast! ½ references < 8 yrs. Chemistry ½ references < 5 yrs. Physics Textbooks out dated when published Practical implications in the digital library What about computer science? To think about: Is it really outdated-ness that is measured or something else?
14	ISI Impact Factor
15	Half Life Decay in Action
16	Expected Citation Rates From a large sample can calculate expected rates of citations For journals vs. conferences For specific journals vs. other ones Can find a researcher’s productivities against this specific rate Basis for promotion
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18	Linkage Citations in scientific papers are important: Demonstrate awareness of background Prior work being built upon Substantiate claims Contrast to competing work Any other reasons? One of the main reasons # of citations by themselves not a good rationale for evaluation.
19	Non-trivial to unify citations Citations have different styles: Citeseer tried edit distance, structured field recognition Settled on _______________________________________________________________ More work to be done here: OpCit GPL code
20	Computational Analysis of Links If we know what type of citations/links exist, that can help: In scientific articles: In calculating impact In relevance judgment (browsing à survey paper) ______________________________ In DL item retrieval: In classifying items pointed by a link _________________________
21	Calculating citation types Teufel (00): creates Rhetorical Document Profiles Capitalizes on fixed structure and argumentative goals in scientific articles (e.g. Related Work) Uses _______________________________ of citation to classify (e.g., In constrast to [1], we …) a zone
22	Using link text for classification The link text that describes a page in another page can be used for classification. Amitay (98) extended this concept by ranking nearby text fragments using (among other things) __________. XXXX: …. … .. … .. … … … .. …. XXX, …. … .. … … … XXXX[ … ] [ … ] [ …. ]
23	Ranking related papers in retrieval Citeseer uses two forms of relatedness to recommend “related articles”: TF × IDF If above a threshold, report it CC (Common Citation) × IDF CC = Bibliographic Coupling If two papers share a rare citation, this is more important than if they share a common one.
24	Citation Analysis Deciding which (web sites, authors) are most prominent
25	Citation Analysis Despite shortcomings, still useful Citation links viewed as a DAG Incoming and outgoing links have different treatments
26	Prominence Consider a node prominent if its ties make it particularly visible to other nodes in the network (adapted from WF, pg 172) Centrality – no distinction on incoming or outgoing edges (thus directionality doesn’t matter. How involved is the node in the graph. Prestige – “Status”. Ranking the prestige of nodes among other nodes. In degree counts towards prestige.
27	Centrality How central is a particular Graph? Node? Graph-wide measures assist in comparing graphs, subgraphs
28	Node Degree Centrality Degree (In + Out) Normalized Degree (In+Out/Possible) What’s max possible? Variance of Degrees
29	Distance Centrality Closeness = minimal distance Sum of shortest paths should be minimal in a central graph ____________ = subset of nodes that have minimal sum distance to all nodes. What about disconnected components?
30	Betweenness Centrality A node is central iff it lies between other nodes on their shortest path. If there is more than one shortest path, Treat each with equal weight Use some weighting scheme Inverse of path length
31	References (besides readings) Bollen and Luce (02) Evaluation of Digital Library Impact and User Communities by Analysis of Usage Patterns http://www.dlib.org/dlib/june02/bollen/06bollen.html Kaplan and Nelson (00) Determining the publication impact of a digital library http://download.interscience.wiley.com/cgi-bin/fulltext?ID=69503874&PLACEBO=IE.pdf&mode=pdf Wasserman and Faust (94) Social Network Analysis (on reserve)
32	Things to think about What’s the relationship between these three laws (Bradford, Zipf-Yule-Pareto and Lotka)? How would you define the three zones in Bradford’s law?