Part VI Terms and Interpretation, 20 Interpretation of Written Contracts

Commercially, this is the most important field of contractual law. In recent decades, English courts have declared that the task is to interpret written contracts (also known as ‘construction’) with sensitivity to shared purposes and aims. The courts have regard to the factual matrix within which the contract has arisen and to issues of business or commercial common sense. The courts will also read contractual wording without misplaced pedantry. Under the rubric of ‘constructive construction’, judges are prepared to rearrange text when it is clear that inapposite language has been used and it is also objectively obvious what the shared intention must have been. This process is illuminated by text, context, and (where there is genuine ambiguity) to commercial common sense, but not by deep reference to background party discussion or private opinion. Thus there are three evidential bars: the courts will not admit evidence of a party’s subjective intent or understanding; secondly, evidence of negotiations is inadmissible (but such evidence will be fundamental if a plea of rectification is made, on which chapter 21); thirdly, post-formation conduct is inadmissible (unless there has been a variation or estoppel by convention; on the latter [2.58]).

Sentiment Research on Twitter Data

The scale of social network data that is being generated is increasing exponentially day by day. Public and private opinion of various subjects or issues are expressed in social media. Sentiment analysis is a method of analyzing the sentiment of a statement that it embodies. Twitter is one of the social medias that is gaining popularity nowadays and most people are using this platform to express their opinions. Sentiment analysis on Twitter is an application of analyzing the sentiment of twitter data(tweets) conveyed by the user. The research on this problem statement has grown consistently. The main reason behind this is the challenging format of tweets that are posted, and it makes the processing difficult. The tweet format would be the number of characters, slangs, abbreviations, emojis, http links and so on. In this paper the aim to describe the methodologies adopted, the process and models applied, along with a generalized approach using python. Sentiment analysis aims to determine or measure the attitude of the writer with respect to some topic.

Sentiment Analysis for Tweets using Patterns and Strategies to Detect the Genuineness of Tweets

Sentiment analysis related with distinguishing and classifying opinions or sentiments expressed in given text. Social media is completing a colossal quality of wealthy knowledge within the type of tweets, standing updates, diary posts etc. Sentiment analysis of this user generated knowledge is incredibly helpful in knowing the opinion of the gang. Twitter sentiment analysis is troublesome compared to general sentiment analysis thanks to the presence of slang words and misspellings. Knowledge base approach and Machine learning approach square measure the 2 methods used for analyzing sentiments from the text. Public and private opinion a few wide range of subjects’ square measure expressed and unfold frequently via numerous social media. Twitter offers organizations quick and effective thanks to analyze customers' view toward the crucial to success within the market place. Developing a program for sentiment analysis is an approach to be accustomed computationally live customers' perceptions. This project cognitive content together with varied patterns for tweets along a side multiple strategies to discover the sentiment class expressed in a very tweet and if a tweet is real or not. We proposed work to classify sentiments of tweets from people to determine if people are happy, sad, angry, etc. about particular topic. Also the purpose of the work is to check genuineness of tweets so that rumors about any topics can be detected and mitigated. This approach can be used in various fields further as like detecting people sentiment about particular social issues. Also fake tweets and rumors which may further exploit to social issues like riots, religion complexities can be removed. To achieve these goals and fetch tweets we used Twit4j API and various techniques such as NLP, TF-IDF, and Sentiment Classifications are applied to get results accordingly. We had maintained our own database of words for dictionary purpose as well as have been used OpenApache NLP with their predefined dictionaries

Successful PR-support means concerning the public image and business reputation of the corporate press

This article covers the PR-support of the public image and business reputation using the example of the corporate magazine “Oilfield Review”; this magazine belongs to Schlumberger — an oilfield services company. Schlumberger is an international supplier of technologies concerning the development of program products for oil and gas exploration, oil production and geophysical research. Among many other regions, Schlumberger operates in the Khanty-Mansi Autonomous Okrug as well. Considering the aspects of corporate press, it is worth noting that a special emphasis has to be put on the «effectiveness» criterion. Efficiency of resource application of corporate mass media and its ability to reach the goal of corporate communication project, this is what has to be understood under the term of «effectiveness». Corporate press is the means of outreach activities aimed at the public opinion of different types of groups within the company, that includes: employees, business partners, customers, governmental authorities and so on. The indirect commercial link between the cost of publishing of corporate media outlets and the increase in revenue of the company arises through the activities of the target audience. The effectiveness of PR-support of public image and business reputation of corporate press is measured by the quality and effectiveness of the process results aimed at the target audience. The effectiveness of PR-support is measured by the following criteria: the level of demand for corporate publication; the level of understanding of the information by the public; the level of information impact on the private opinion of the readers concerning the activities of the company; the level of information impact on the behavior of the intended readers. This article concerns the consecutive evaluation of a Schlumberger corporate media outlet «Oilfield Review», its PR-support effectiveness in the following aspects: its structure, design, the quality of the articles, the quality of the pictures, the level of interactive technologies, and the system of key messages.

The Demise of the Journal Ranking: A Victory for Common Sense

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