Research on the Use of Network Language in Chinese Government Microblogs

The emergence of government microblog not only widens the channels for the people to participate in politics,but also is of great significance for the government to understand public opinion and promote the process of political democratization.In recent years,the frequency of network language in Chinese government microblog has gradually increased.Taking the“Beijing release”official microblog as an example,this paper discusses the characteristics of network language,and puts forward some suggestions on the use of network language in government microblog:in terms of syllables,network language below three syllables should be selected to meet the requirements of short length of government microblog;In terms of part of speech,network terms such as nouns,verbs and adjectives can express emotional attitude and value judgment;In terms of emotion and style,emotional attitude forms such as intimacy,love and respect are selected.In addition,the norms of network language in government microblog can not be generalized.We should not only pay attention to the expression effect,but also set foot in multiple disciplines and fields.

A DILEMMA FOR LANGUAGE TESTERS IN A NETWORK AGE

With the rapid development of silicon chip tech-nology,web-based instruction(WBI)and computer-ized adaptive testing(CAT)will be the new trends inthe field of language teaching and testing.We assumethat only when teaching and testing share the sameview about the nature of language and language learn-ing can testing exercise a beneficial backwash effect onteaching.However,WBI and CAT prove to be basedon opposite theories of language and language learn-ing.While WBI believes in constructivism,CAT cor-responds to structuralism and behaviorism.This situ-ation places language testers in a dilemma,for if theyfollow the trend,testing will go against teaching.Butif they give up CAT,it is very difficult to substituteanother testing system possessing so many advantages.This paper illustrates in detail why WBI and CAT areto become the new trends in teaching and testing,ex-plains clearly the discrepancy between WBI and CAT intheory and their objectives and finally attempts toprovide a solution to help the language testers out ofthe dilemma.

Punjabi DeConverter for generating Punjabi from Universal Networking Language

DeConverter is core software in a Universal Networking Language(UNL) system.A UNL system has EnConverter and DeConverter as its two major components.EnConverter is used to convert a natural language sentence into an equivalent UNL expression,and DeConverter is used to generate a natural language sentence from an input UNL expression.This paper presents design and development of a Punjabi DeConverter.It describes five phases of the proposed Punjabi DeConverter,i.e.,UNL parser,lexeme selection,morphology generation,function word insertion,and syntactic linearization.This paper also illustrates all these phases of the Punjabi DeConverter with a special focus on syntactic linearization issues of the Punjabi DeConverter.Syntactic linearization is the process of defining arrangements of words in generated output.The algorithms and pseudocodes for implementation of syntactic linearization of a simple UNL graph,a UNL graph with scope nodes and a node having un-traversed parents or multiple parents in a UNL graph have been discussed in this paper.Special cases of syntactic linearization with respect to Punjabi language for UNL relations like 'and','or','fmt','cnt',and 'seq' have also been presented in this paper.This paper also provides implementation results of the proposed Punjabi DeConverter.The DeConverter has been tested on 1000 UNL expressions by considering a Spanish UNL language server and agricultural domain threads developed by Indian Institute of Technology(IIT),Bombay,India,as gold-standards.The proposed system generates 89.0% grammatically correct sentences,92.0% faithful sentences to the original sentences,and has a fluency score of 3.61 and an adequacy score of 3.70 on a 4-point scale.The system is also able to achieve a bilingual evaluation understudy(BLEU) score of 0.72.