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Table 1 Properties of different types of users

From: Detecting problematic transactions in a consumer-to-consumer e-commerce network

Seed user type

Normal

Fictive

Underwear

Medicine

Weapon

Number of seed users

999

440

468

469

416

Number of transactions involving the seed user

151,021

66,215

151,278

92,497

81,970

Total number of transactions

27,683,860

850,739

2,325,898

925,361

533,963

\(k_i=1\)

587 (58.8%)

8 (1.8%)

3 (0.6%)

2 (0.4%)

5 (1.2%)

Mean (\(k_i \mid k_i\ge 2\))

195.0

138.3

297.8

184.2

179.7

Median (\(k_i \mid k_i\ge 2\))

77.5

61.0

170.0

97.0

86.0

\(s_i=1\)

587 (58.8%)

8 (1.8%)

3 (0.6%)

2 (0.4%)

5 (1.2%)

Mean (\(s_i \mid s_i\ge 2\))

365.1

153.3

325.3

198.1

199.4

Median (\(s_i \mid s_i\ge 2\))

89.0

66.5

175.0

100.0

90.0

\(s_i\ge 2\)

412

432

465

467

411

\(s_i/k_i=1\)

97 (23.5%)

97 (22.5%)

86 (18.5%)

156 (33.4%)

121 (29.4%)

Mean (\(s_i/k_i \mid s_i/k_i>1\))

1.413

1.135

1.055

1.066

1.092

Median (\(s_i/k_i \mid s_i/k_i>1\))

1.124

1.059

1.03

1.031

1.055

\(k_i\ge 2\)

412

432

465

467

411

\({{\mathrm {SP}}}_i=1\)

157 (38.1%)

15 (3.5%)

21 (4.5%)

16 (3.4%)

17 (4.1%)

\(k_i^{{\mathrm {out}}}=1\)

118 (28.6%)

21 (4.9%)

2 (0.4%)

2 (0.4%)

9 (2.2%)

\(s_i\ge 2\)

412

432

465

467

411

\({\mathrm {WSP}}_i=1\)

157 (38.1%)

15 (3.5%)

21 (4.5%)

16 (3.4%)

17 (4.1%)

\(s_i^{{\mathrm {out}}}=1\)

118 (28.6%)

14 (3.2%)

2 (0.4%)

2 (0.4%)

9 (2.2%)

\(k_i\ge 2\)

412

432

465

467

411

\(C_i=0\)

118 (28.6%)

152 (35.2%)

108 (23.2%)

154 (33.0%)

128 (31.1%)

Mean (\(C_i \mid C_i>0\))

\(8.554\times 10^{-3}\)

\(8.348\times 10^{-3}\)

\(9.500\times 10^{-4}\)

\(2.231\times 10^{-3}\)

\(3.810\times 10^{-3}\)

Median (\(C_i \mid C_i>0\))

\(2.411\times 10^{-3}\)

\(2.039\times 10^{-3}\)

\(5.288\times 10^{-4}\)

\(6.494\times 10^{-4}\)

\(1.337\times 10^{-3}\)

\({\mathrm {Tr}}_i\ge 2\)

262

241

317

251

244

\(m_i=0\)

17 (6.5%)

27 (11.2%)

54 (17.0%)

44 (17.5%)

32 (13.1%)

\(m_i=1\)

12 (4.6%)

9 (3.7%)

4 (1.3%)

6 (2.4%)

11 (4.5%)

Mean (\(m_i \mid m_i>0\))

\(8.554\times 10^{-3}\)

\(8.348\times 10^{-3}\)

\(9.500\times 10^{-4}\)

\(2.231\times 10^{-3}\)

\(3.810\times 10^{-3}\)

Median (\(m_i \mid m_i>0\))

\(2.411\times 10^{-3}\)

\(2.039\times 10^{-3}\)

\(5.288\times 10^{-4}\)

\(6.494\times 10^{-4}\)

\(1.337\times 10^{-3}\)

\({\mathrm {FF}}_i+{\mathrm {CY}}_i\ge 1\)

294

280

357

313

283

\({\mathrm {CYP}}_i=0\)

234 (79.6%)

188 (67.1%)

222 (62.2%)

227 (72.5%)

202 (71.4%)

Mean (\({\mathrm {CYP}}_i \mid {\mathrm {CYP}}_i>0\))

\(1.987\times 10^{-2}\)

\(7.367\times 10^{-2}\)

\(6.739\times 10^{-2}\)

\(8.551\times 10^{-2}\)

\(5.544\times 10^{-2}\)

Median (\({\mathrm {CYP}}_i \mid {\mathrm {CYP}}_i>0\))

\(1.521\times 10^{-2}\)

\(4.481\times 10^{-2}\)

\(3.396\times 10^{-2}\)

\(3.822\times 10^{-2}\)

\(3.618\times 10^{-2}\)

  1. In the first column, Mean (\({\mathrm {A}}\mid {\mathrm {B}}\)), for example, represents the mean of A conditioned on B. Unless the first column mentions the conditional mean, median, or the number of transactions, the numbers reported in the table represent the number of users