translate the following paragraphs into Chinese.  With 72 real fraud cases at hand, we first classified the fabricated identities into 
five types on the basis of the discursive practices used by the con artists. Then 
we categorised the discursive practices used in fraud cases according to Chen’s 
(2018) framework and calculated the percentage of each discursive practice by 
dividing its number of occurrences by the total cases of fraud (i.e. 72). Afterwards, 
we further categorised each discursive practice according to its manifestations 
and calculated their percentages by dividing their number of occurrences by the total cases of fraud (i.e. 72). Note that a category may have several manifestations. 
For instance, a con artist may use both a polite form such as nin (honorific ‘you’) 
and an intimate term of address such as dajie (‘big sister’); in this case, we would￾count one occurrence for the category ‘polite term’ and another one occurrence 
for the category ‘intimate term’. For the details about the percentage of each type 
of discursive practice as well as those of its manifestations, refer to Table 2 (shown 
in Section 5.1).
After the quantitative analysis, we chose one example from each identity cat￾egory and studied the reciprocal relationship between language and identity, 
based on the framework by Chen (2018). These five cases were picked out because 
the fraud language in each can be reconstructed to the fullest degree, so that we 
can present a clear and comprehensible analysis in the study. Of the five examples, 
Case (3) shows how a con artist failed in his attempt. It was deliberately singled 
out to display mismatch between identities and discursive practices.
In the analysis, we reconstructed the communications between the con art￾ists and their targets with background information. We quoted whatever they 
recalled had been said between them and arranged their utterances according to 
the time sequence. The background information provided within brackets was 
extracted from the narration. Though these dialogues may not be exactly the 
same as what actually occurred, they are close enough to reality to warrant our 
analysis.
In addition, ten more cases, together with the previous five, were shown to 
explicate the mechanism behind the deceptive identity construction. A table of 
details was given on what con artists’ fabricated identities were, where they con￾tacted the targets, and what excuses they used for their frauds. The above-men￾tioned recollections, comments and quotations were used to support our argu￾ment.
5. Types of fabricated identities and their discursive practices
This section reports the findings that have emerged from our data examination.
5.1 General findings
By examining the data, we discovered five types of identities con artists often 
fabricated. They were: (i) ‘victim’, which could evoke sympathy (e.g. a woman 
whose wallet was stolen; a pregnant woman who was hit by a car); (ii) ‘friend/
kin’, which could attract one’s affection (e.g. son, old friend, man seeking a part￾ner); (iii) ‘clerk’, which provides business services to the public (e.g. operators in 
telecom institutions); (iv) ‘official’, which presumes authority and accountability (e.g. officials in a judicial department, a police officer); and (v) ‘resourceful person’, which presumes high status financially or spiritually (e.g. the brother of a 
board chairman, a person with a degree in higher education from a developed 
country, a master of Buddhism, the daughter of a real-estate shareholder). The 
results partly echo Freiermuth’s (2011) study on fraud email, in which he notices 
that the scammer’s commonly projected identities are as a refugee, a financial 
officer, a lottery official, and a company member offering a too-good-to-be-true 
job. A refugee belongs to the victim category, and the other three belong to the 
resourceful person category. Since the current study examines various types of 
frauds, it is able to identify more specific identity categories.