Can web indicators be used to estimate the citation impact of conference papers in engineering?

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Although citation counts are widely used to support research evaluation, they can only reflect academic impacts, whereas research can also be useful outside academia. There is therefore a need for alternative indicators and empirical studies to evaluate them. Whilst many previous studies have investigated alternative indicators for journal articles and books, this thesis explores the importance and suitability of four web indicators for conference papers. These are readership counts from the online reference manager Mendeley and citation counts from Google Patents, Wikipedia and Google Books. To help evaluate these indicators for conference papers, correlations with Scopus citations were evaluated for each alternative indicator and compared with corresponding correlations between alternative indicators and citation counts for journal articles. Four subject areas that value conferences were chosen for the analysis: Computer Science Applications; Computer Software Engineering; Building & Construction Engineering; and Industrial & Manufacturing Engineering. There were moderate correlations between Mendeley readership counts and Scopus citation counts for both journal articles and conference papers in Computer Science Applications and Computer Software. For conference papers in Building & Construction Engineering and Industrial & Manufacturing Engineering, the correlations between Mendeley readers and citation counts are much lower than for journal articles. Thus, in fields where conferences are important, Mendeley readership counts are reasonable impact indicators for conference papers although they are better impact indicators for journal articles. Google Patent citations had low positive correlations with citation counts for both conference papers and journal articles in Software Engineering and Computer Science Applications. There were negative correlations for both conference papers and journal articles in Industrial and Manufacturing Engineering. However, conference papers in Building and Construction Engineering attracted no Google Patent citations. This suggests that there are disciplinary differences but little overall value for Google Patent citations as impact indicators in engineering fields valuing conferences. Wikipedia citations had correlations with Scopus citations that were statistically significantly positive only in Computer Science Applications, whereas the correlations were not statistically significantly different from zero in Building & Construction Engineering, Industrial & Manufacturing Engineering and Software Engineering. Conference papers were less likely to be cited in Wikipedia than journal articles were in all fields, although the difference was minor in Software Engineering. Thus, Wikipedia citations seem to have little value in engineering fields valuing conferences. Google Books citations had positive significant correlations with Scopus-indexed citations for conference papers in all fields except Building & Construction Engineering, where the correlations were not statistically significantly different from zero. Google Books citations seemed to be most valuable impact indicators in Computer Science Applications and Software Engineering, where the correlations were moderate, than in Industrial & Manufacturing Engineering, where the correlations were low. This means that Google Book citations are valuable indicators for conference papers in engineering fields valuing conferences. Although evidence from correlation tests alone is insufficient to judge the value of alternative indicators, the results suggest that Mendeley readers and Google Books citations may be useful for both journal articles and conference papers in engineering fields that value conferences, but not Wikipedia citations or Google Patent citations.Tetfund, Nigeri

Rationality authority for provable rational behavior

Players in a game are assumed to be totally rational and absolutely smart. However, in reality all players may act in non-rational ways and may fail to understand and find their best actions. In particular, participants in social interactions, such as lotteries and auctions, cannot be expected to always find by themselves the "best-reply" to any situation. Indeed, agents may consult with others about the possible outcome of their actions. It is then up to the counselee to assure the rationality of the consultant's advice. We present a distributed computer system infrastructure, named rationality authority, that allows safe consultation among (possibly biased) parties. The parties' advices are adapted only after verifying their feasibility and optimality by standard formal proof checkers. The rationality authority design considers computational constraints, as well as privacy and security issues, such as verification methods that do not reveal private preferences. Some of the techniques resembles zero-knowledge proofs. A non-cooperative game is presented by the game inventor along with its (possibly intractable) equilibrium. The game inventor advises playing by this equilibrium and offers a checkable proof for the equilibrium feasibility and optimality. Standard verification procedures, provided by trusted (according to their reputation) verification procedures, are used to verify the proof. Thus, the proposed rationality authority infrastructure facilitates the applications of game theory in several important real-life scenarios by the use of computing systems

Rationality authority for provable rational behavior

Players in a game are assumed to be totally rational and absolutely smart. However, in reality all players may act in non-rational ways and may fail to understand and find their best actions. In particular, participants in social interactions, such as lotteries and auctions, cannot be expected to always find by themselves the “best-reply” to any situation. Indeed, agents may consult with others about the possible outcome of their actions. It is then up to the counselee to assure the rationality of the consultant’s advice. We present a distributed computer system infrastructure, named rationality authority, that allows safe consultation among (possibly biased) parties. The parties’ advices are adapted only after verifying their feasibility and optimality by standard formal proof checkers. The rationality authority design considers computational constraints, as well as privacy and security issues, such as verification methods that do not reveal private preferences. Some of the techniques resembles zero-knowledge proofs. A non-cooperative game is presented by the game inventor along with its (possibly intractable) equilibrium. The game inventor advises playing by this equilibrium and offers a checkable proof for the equilibrium feasibility and optimality. Standard verification procedures, provided by trusted (according to their reputation) verification procedures, are used to verify the proof. Thus, the proposed rationality authority infrastructure facilitates the applications of game theory in several important real-life scenarios by the use of computing systems