TY - GEN
T1 - Data mining the underlying trust in the US Congress
AU - Wu, Sissi Xiaoxiao
AU - Wai, Hoi To
AU - Scaglione, Anna
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/4/19
Y1 - 2017/4/19
N2 - In this paper, we mine the US congress voting records to extract the latent information about the trust among congress members. In particular, we model the Senate as a social network and the voting process as a set of outcomes of the underlying opinion dynamics which we assume follow a corrupted DeGroot model. The transition matrix in the opinion dynamics model is the trust matrix among Senators that we estimate. Our methodology is to first cluster the voting bills into different groups, and then obtain the Senators' opinions about the theme of each cluster, by performing a weighted Bernoulli sampling on the binary voting results. A key characteristic of the US congress is that most of the Senators stick with their own ideology. In view of this, we assign the role of stubborn nodes to some Senators, since their existence can facilitate estimating the trust matrix. In fact, we find the trust matrix by solving a linear regression problem, and then analyze the underlying latent information. Interestingly, our numerical results are quite consistent with the common intuition. More importantly, the trust information extracted can help understand the underlying relationship in the Senate and offer insights for devising political strategies.
AB - In this paper, we mine the US congress voting records to extract the latent information about the trust among congress members. In particular, we model the Senate as a social network and the voting process as a set of outcomes of the underlying opinion dynamics which we assume follow a corrupted DeGroot model. The transition matrix in the opinion dynamics model is the trust matrix among Senators that we estimate. Our methodology is to first cluster the voting bills into different groups, and then obtain the Senators' opinions about the theme of each cluster, by performing a weighted Bernoulli sampling on the binary voting results. A key characteristic of the US congress is that most of the Senators stick with their own ideology. In view of this, we assign the role of stubborn nodes to some Senators, since their existence can facilitate estimating the trust matrix. In fact, we find the trust matrix by solving a linear regression problem, and then analyze the underlying latent information. Interestingly, our numerical results are quite consistent with the common intuition. More importantly, the trust information extracted can help understand the underlying relationship in the Senate and offer insights for devising political strategies.
KW - Data mining
KW - Senator
KW - Social network
KW - Trust analysis
KW - US congress
UR - http://www.scopus.com/inward/record.url?scp=85019256100&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019256100&partnerID=8YFLogxK
U2 - 10.1109/GlobalSIP.2016.7906032
DO - 10.1109/GlobalSIP.2016.7906032
M3 - Conference contribution
AN - SCOPUS:85019256100
T3 - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
SP - 1202
EP - 1206
BT - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
Y2 - 7 December 2016 through 9 December 2016
ER -