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This paper aims to investigate the multiple language support features in internet search engines. The diversity of the internet is reflected not only in its users, information formats and information content, but also in the languages used. As more and more information becomes available in different languages, multiple language support in a search engine becomes more important.

The first step of this study is to conduct a survey about existing search engines and to identify search engines with multiple language support features. The second step is to analyse, compare, and characterise the multiple language support features in the selected search engines against the proposed five basic evaluation criteria after they are classified into three categories. Finally, the strengths and weaknesses of the multiple language support features in the selected search engines are discussed in detail.

The findings reveal that Google, EZ2Find, and Onlinelink respectively are the search engines with the best multiple language support features in their categories. Although many search engines are equipped with multiple language support features, an indispensable translation feature is implemented in only a few search engines. Multiple language support features in search engines remain at the lexical level.

The findings of the study will facilitate understanding of the current status of multiple language support in search engines, help users to effectively utilise multiple language support features in a search engine, and provide useful advice and suggestions for search engine researchers, designers and developers.

Purpose – People do not just interact, with each other; rather, they engage with each other using the visual and verbal instrumentations of communication at their disposal, constructing meaningful and intelligible conversations with differing degrees of precision of intention and clarity of expression. In doing this, they employ the “fundamental features of language,” described in various semiotic and structuralist theories.

Methodology – Here, we synthesize and integrate the key aspects of these language theories in an attempt to apply them to everyday conversations. The language features in question are routinely put into play by human agents to convey attitudes, emotions, opinions, and information and to achieve an engagement with the other.

Findings – Human relations, expansive in their range and intricate in their forms, demand complex instrumentations with which to conduct them. These instrumentations are essential features of the linguistic socialization of human agents, integral to both memory and habits of speech.

This study aims to explore the communicative features of teacher talk in English for General Purposes (EGP) vs. English for Academic Purposes (EAP) classes in Iranian contexts based on the Self-Evaluation Teacher Talk (SETT) framework.

For the purposes of this study, EAP and EGP classes run by three language instructors and three content instructors were observed and interviews with teacher participants were conducted. The data were analyzed by content analysis, and emerging overarching themes were recorded.

The findings of this study indicate that the translation of texts into Persian was the dominant theme in classes run by content instructors who were less aware of the communicative features of teacher talk. However, one of the content instructors who was familiar with the communicative features of teacher talk as well as general language instructors were found to be highly aware of the potential of their teacher talk to encourage communication in his classes. The innovative and communicative features in the language/content instructor suggest the importance of teacher agency in bringing change in education at the micro-level. This study has implications for various agencies involved in teaching EAP, EGAP and English for Specific Purposes (ESAP), raising awareness regarding the communicative features of teacher talk as a driving force leading learners and teachers to more communicative opportunities in language classrooms. The findings suggest that teacher talk is an essential component of classroom discourse, shaping students' linguistic and academic development, and that teacher agency is crucial in promoting communicative opportunities in language education. To boost communication, the authors recommend translanguaging with a focus on both communication and optimal use of the mother tongue in EAP classes.

There is little empirical evidence on the communicative aspects of teacher talk in higher education. This study can inspire more parallel research on EAP settings in higher education with a focus on communication and teacher talk features.

The purpose of this paper is to investigate image search and retrieval problems in selected search engines in relation to Persian writing style challenges.

This study is an applied one, and to answer the questions the authors used an evaluative research method. The aim of the research is to explore the morphological and semantic problems of Persian language in connection with image search and retrieval among the three major and widespread search engines: Google, Yahoo and Bing. In order to collect the data, a checklist designed by the researcher was used and then the data were analyzed by descriptive and inferential statistics.

The results indicate that Google, Yahoo and Bing search engines do not pay enough attention to morphological and semantic features of Persian language in image search and retrieval. This research reveals that six groups of Persian language features include derived words, derived/compound words, Persian and Arabic Plural words, use of dotted T and the use of spoken language and polysemy, which are the major problems in this area. In addition, the results suggest that Google is the best search engine of all in terms of compatibility with Persian language features.

This study investigated some new aspects of the above-mentioned subject through combining morphological and semantic aspects of Persian language with image search and retrieval. Therefore, this study is an interdisciplinary research, the results of which would help both to offer some solutions and to carry out similar research on this subject area. This study will also fill a gap in research studies conducted so far in this area in Farsi language, especially in image search and retrieval. Moreover, findings of this study can help to bridge the gap between the user’s questions and search engines (systems) retrievals. In addition, the methodology of this paper provides a framework for further research on image search and retrieval in databases and search engines.

The purpose of this paper is to investigate the impact of a dual medium/content context – the one offered by the online Twitter communication (medium-context) of reporting on elite sports (content-context) – on traditional conceptualizations of genderlect.

A quantitative content analysis, coding for a variety of traditional gendered language markers – was conducted on the tweets of male and female reporters who covered the men’s and women’s NCAA final four basketball tournaments.

Consistent with tenets of social role theory, the duel medium/content context of Twitter and sports produces several language patterns that frustrate attempts to categorize language markers according to traditional conceptualizations of genderlect and thus provides support for a redefinition of genderlect.

This paper’s findings suggest that people adapt their communication patterns to match the context in which they communicate. Whether adaptation takes place with conscious effort or as a natural byproduct of moving from one context to another remains to be discovered. Advice to female sports journalists on being vigilant against unwittingly undermining their credibility and perceived expertise is offered. This inquiry allows researchers to study sociology through sport.

This paper demonstrates that online environments can allow for traditional gender roles and expectations to be challenged and broken down, but some genderlect features appear tenacious and could undermine attempts to break down gender barriers.

If sport mirrors society, then the same communication adaptations that appear in the online environmental context of reporters’ tweets about sport should appear in other societal contexts.

Few studies have investigated differences in reporting by gender, and fewer have investigated differences in sports reporting by gender. Fewer, if any, have investigated differences in sports reporting by gender through Twitter.

The purpose of this paper is to design organization message content strategies and analyse their information diffusion on the microblogging website, Twitter.

Using data from 29 brands and 9392 tweets, message strategies on twitter are classified into four strategies. Using content analysis all the tweets are classified into informational strategy, transformational strategy, interactional strategy and promotional strategy. Additionally, the information diffusion for the developed message strategies was explored. Furthermore, message content features such as text readability features, language features, Twitter-specific features, vividness features on information diffusion are analysed across message strategies. Additionally, the interaction between message strategies and message features was carried out.

Finding reveals that informational strategies were the dominant message strategy on Twitter. The influence of text readability features language features, Twitter-specific features, vividness features that influenced information diffusion varied across four message strategies.

This study offers a completely novel way for effectively analysing information diffusion for branded tweets on Twitter and can show a path to both researchers and practitioners for the development of successful social media marketing strategies.

As convenience and anonymity, people with mental illness are increasingly willing to communicate and share information through social media platforms to receive emotional and spiritual support. The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.

Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.

The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.

This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.

It is not possible to remember more than a few command languages accurately. If a command language is used infrequently it is very easy to forget the commands or make mistakes because the command is entered incorrectly. To solve this problem a quick reference chart of the main searching and printing commands and support features for the following command languages has been compiled — Basis, BRS, Dialog, Elhill, Eurolanguage, Grips/Dirs, Orbit, Quest, Questel. This paper describes the compilation of the chart and discusses the differences between command languages.

Service‐oriented architecture is becoming increasingly important for healthcare delivery as it assures seamless integration internally between various teams and departments, and externally between healthcare organizations and their partners. In order to make healthcare more efficient and effective, we need to understand and evaluate its processes, and one way of achieving that is through process modeling. Modeling healthcare processes within a service‐oriented environment opens up new perspectives and raises challenging questions. The purpose of this paper is to investigate one of these questions, namely the suitability of web service orchestration and choreography, two closely related but fundamentally different methodologies for modeling web service‐based healthcare processes.

The authors use a case‐based approach that first developed a set of 12 features for modeling healthcare processes and then used the features to compare orchestration and choreography for modeling part of the scheduled workflow.

The findings show that neither methodology can, by itself, meet all healthcare modeling requirements in the context of the case study. The appropriate methodology must be selected after consideration of the specific modeling needs. The authors identified usability, capabilities, and evolution as three key considerations to assist with selection of a methodology for healthcare process modeling. Further, sometimes one method will not meet all modeling needs and hence the authors recommend combining the two methodologies in order to harness the benefits of modeling healthcare processes in a service‐oriented environment.

Although literature exists on process modeling of web services for healthcare, there are no criteria describing necessary features for micro‐level modeling, nor is there a comparison of the two leading service composition methodologies within the healthcare context. This paper provides some necessary formalization for process modeling in healthcare.

Large-Scale Assessments in Germany have shown that language-minority students as well as students with special educational needs (SEN) perform significantly less well than language-majority students or students without SEN. This performance gap may be related to a limited accessibility of the tests. One way to test whether assessments allow all students to demonstrate their knowledge in a comparable way is the analysis of differential item functioning (DIF). In this chapter, we evaluate DIF coefficients in order to examine group-specific difficulties in reading comprehension for language-minority students and students with SEN in the German National Educational Assessment.

In the first study, we investigate the assessment of reading literacy of language-minority learners and German monolinguals from low-SES families. We found only a few items with moderate DIF and no items with large DIF. This indicates that the reading assessment was equally valid for second-language learners and German monolingual students.

In our second study, we report about the psychometrically successful development of easy and more accessible reading tasks for students with SEN. Further analyses showed that DIF predominantly occurred in items that captured contents that are not necessarily covered in literacy instruction targeted at students with SEN.