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The purpose of this paper is to handle the anaphors through anaphora resolution in aspect-oriented sentiment analysis. Sentiment analysis is one of the predictive analytics of social media. In particular, the social media platform Twitter is an open platform to post the opinion by subscribers on contextual issues, events, products, individuals and organizations.

The sentiment polarity assessment is not deterministic to conclude the opinion of the target audience unless the polarity is assessed under diversified aspects. Hence, the aspect-oriented sentiment polarity assessment is a crucial objective of the opinion assessment over social media. However, the aspect-oriented sentiment polarity assessment often influences by the curse of anaphora resolution.

Focusing on these limitations, a scale to estimate the aspects oriented sentiment polarity under anaphors influence has been portrayed in this article. To assess the aspect-based sentiment polarity of the tweets, the anaphors of the tweets have been considered to assess the weightage of the tweets toward the sentiment polarity.

The experimental study presents the performance of the proposed model by comparing it with the contemporary models, which are estimating the sentiment polarity tweets under anaphors impact.

Although the structure of texts and the way they are produced and understood are active areas for research in a range of disciplines — linguistics, psychology, artificial intelligence and information science — this research has not yet produced convincing computer‐based solutions to the problem of producing abstracts of technical papers. Genuinely knowledge‐based approaches are probably furthest from producing practical results, because of the amount of background knowledge that they presuppose and because of the difficulty in principle of finding appropriate representations and processes. After reviewing the kinds of structure in abstracts that seem pertinent to the abstracting problem, we discuss a rule‐based approach that requires a relatively simple knowledge base, partitioned into two sets of rules: one for recognising textual fragments that explicitly signal the document topic, and another for detecting when referring expressions (especially pronouns) are linked to objects mentioned or evoked in a different sentence. These two rule sets are used in a method of exctracting from text to produce a paragraph which can function as an abstract, pioneered by Paice at the University of Lancaster. The second stage of the method is designed to ensure that sentences extracted in the first do not contain any references to parts of the text that have not been extracted, thus ensuring a minimal standard of coherence. In refining these methods, definite noun phases (those beginning with ‘the’) pose a particular problem, which is being addressed in current joint work by Paice and the author.

This corpus-based study provides a descriptive account of the distribution of the polysemous noun nafs in two Arabic varieties, Modern Standard Arabic (MSA) and Classical Arabic (CA). The research objective is to survey the use of nafs as a reflexive marker in local binding domains and as a self-intensifier in NP-adjoined positions.

The consulted corpora are Timespamped JSI Web corpus for MSA and Quran corpus for CA. While attending to corpora size differences, MSA and CA exhibit a pattern of difference and similarity in nafs diffusion.

In the modern variety, nafs is pervasively used as reflexive marker in canonical binding domains, along with a less frequent, yet notable, intensifier user, and these uses are partially and cautiously attributed to the specific genre in which they occur. In CA, nafs is mainly recurrent as a polysemous noun, along with extensive use as a reflexive marker in local binding settings. As an intensifier, nafs is totally non-existent in the CA corpus, in the same way as it is in absentia in VP-constituent extraction in MSA.

Examining whether nafs, as a reflexive marker, deviates from canonical binding in Arabic the way English reflexive pronouns do. Building a general account of this distribution is relevant in understanding the explicit (syntactic) and implicit (discourse-based) dimensions of reflexive marker and self-intensifier processing and interpretation in Arabic as a first and second language.

Many criticisms questioning the role and the efficiency of business consultants have been addressed. However, although a great deal of research has been carried out on business consultancy, little has been written on business consultancy from the consultant's viewpoint. In order to gain a detailed view of the situation from an internal consultant's perspective, an investigation of how business consultants perceive their role and contribution within their clients' organisations was undertaken. Drawing on different perspectives, this study aims to demystify the role of business consultants, and to ascertain how they perceive their role within their clients' organisations.

A series of interviews were conducted, where business consultants were asked to comment on issues related to the nature of the relationship with their clients, the pros and cons of their role and also the amount of control and discretion they exercise over the different projects in which they are engaged. Interview data from 17 business consultants from a variety of fields, such as change management, information technology, corporate finance and human resource, are analysed using an interpretive frame.

The research findings reveal that differences exist between the rather pejorative conclusions of previous research and the conclusions of this study. Whereas previous research highlighted the omnipotence and the more or less deontological practice of consultants, the data analysis from this study concludes that business consultants appear very humble in their approach to their relationship with clients, and believe that moving clients forward is their ultimate goal. The findings also enable the study to demonstrate that business consultants are conscious of the amount of control and discretion that is passed on to them by clients, and do recognise that criticisms of their role can be at times justified.

The study has value for both consultants and clients. The role determinants model presented in the study highlights the main characteristics of the role of business consultants and helps both clients and consultants to rethink their approach to the consulting process.

The citation counts are an important indicator of scholarly impact. The purpose of this paper is to explore the correlation between citations of scientific articles and writing styles of abstracts in papers and capture the characteristics of highly cited papers' abstracts.

This research selected 10,000 highly cited papers and 10,000 zero-cited papers from the WOS (2008-2017) database. The Coh-Metrix 3.0 textual cohesion analysis tool was used to quantify the 108 language features of highly cited and zero-cited paper abstracts. The differences of the indicators with significant differences were analyzed from four aspects: vocabulary, sentence, syntax and readability.

The abstracts of highly cited papers contain more complex and professional words, more adjectives, adverbs, conjunctions and personal pronouns, but fewer nouns and verbs. The sentences in the abstracts of highly cited papers are more complex and the sentence length is relatively longer. The syntactic structure in abstracts of highly cited papers is relatively more complex and syntactic similarities between sentences are fewer. Highly cited papers' abstracts are less readable than zero-cited papers' abstracts.

This study analyses the differences between the abstracts of highly cited and those of zero-cited papers, reveals the common external and deep semantic features of highly cited papers in abstract writing styles, provide suggestions for researchers on abstract writing. These findings can help increase the scientific impact of articles and improve the review efficiency as well as the researchers' abstract writing skills.

In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining.

The prospect of automatically generating abstracts has attracted researchers for some time, but the promise of superseding the human effort has yet to be realized. Surveys the approaches and techniques developed with the view to showing why this is so. Particular emphasis is placed on the requirements for the production of abstracts, which effectively serve their intended function, to show the ways in which this has hampered research in the past. Suggests that progress of automatic abstracting research may come about via the integration of some of the techniques into computerized information retrieval systems. This will allow researchers to shift the aim from reproducing the conventional benefits of abstracts to accentuating the advantages to users of computerized representation of information in large textual databases.

This paper aims to explore the role of storytelling and impression management (IM) through the president’s letter in legitimizing the practices of an electricity company with regard to controversial issues during a period of change.

Drawing on a qualitative case study, this paper examines annual report letters from 1995 to 2013 using a methodological interpretative approach.

By promoting a success story using IM, the presidents give sense to particular actions related with controversial issues and attempt to influence expectations on strategic changes. The findings demonstrate that organizational actors use the flexibility of the president’s letter to tell the story and emphasize its self-laudatory nature. The study highlights that storytelling in these documents can be used to alleviate the tensions created by the inherent contradictions of social structures.

This research is useful for regulatory authorities, users of annual reports and academic researchers, making them attentive of the narratives companies may adopt to protect their legitimacy. The findings shed light on the need to evaluate the credibility of accountability mechanisms and can help stakeholders to develop a more critical view of the president’s letter.

This paper makes a contribution to research on communication issues by expanding literature on accounting and organizational storytelling. By demonstrating how presidents use sensegiving as a means of legitimacy-claiming, this study adds to the literature on legitimating accounts. In doing so, this paper bridges the gap between theories about organizational legitimacy, storytelling and IM. To sum up, the findings serve as an incremental step toward understanding the nature of accountability reporting.

Sentiment analysis and emotion processing are attracting increasing interest in many fields. Computer and information scientists are developing automated methods for sentiment analysis of online text. Most of the studies have focused on identifying sentiment polarity or orientation – whether a document, usually a product or movie review, carries a positive or negative sentiment. It is time for researchers to address more sophisticated kinds of sentiment analysis. This paper aims to evaluate a particular linguistic framework called appraisal theory for adoption in manual as well as automatic sentiment analysis of news text.

The appraisal theory is applied to the analysis of a sample of political news articles reporting on Iraq and the economic policies of George W. Bush and Mahmoud Ahmadinejad to assess its utility and to identify challenges in adopting this framework.

The framework was useful in uncovering various aspects of sentiment that should be useful for researchers, such as the appraisers and object of appraisal, bias of the appraisers and the author, type of attitude and manner of expressing the sentiment. Problems encountered include difficulty in identifying appraisal phrases and attitude categories because of the subtlety of expression in political news articles, lack of treatment of tense and timeframe, lack of a typology of emotions, and need to identify different types of behaviours (political, verbal and material actions) that reflect sentiment.

The study has identified future directions for research in automated sentiment analysis as well as sentiment analysis of online news text. It has also demonstrated how sentiment analysis of news text can be carried out.