A Machine Learning Approach For Opinion Holder Extraction In Arabic Language

Opinion mining aims at extracting useful subjective information from reliable amounts of text. Opinion mining holder recognition is a task that has not been considered yet in Arabic Language. This task essentially requires deep understanding of clauses structures. Unfortunately, the lack of a robust, publicly available, Arabic parser further complicates the research. This paper presents a leading research for the opinion holder extraction in Arabic news independent from any lexical parsers. We investigate constructing a comprehensive feature set to compensate the lack of parsing structural outcomes. The proposed feature set is tuned from English previous works coupled with our proposed semantic field and named entities features. Our feature analysis is based on Conditional Random Fields (CRF) and semi-supervised pattern recognition techniques. Different research models are evaluated via cross-validation experiments achieving 54.03 F-measure. We publicly release our own research outcome corpus and lexicon for opinion mining community to encourage further research

Econometrics meets sentiment : an overview of methodology and applications

The advent of massive amounts of textual, audio, and visual data has spurred the development of econometric methodology to transform qualitative sentiment data into quantitative sentiment variables, and to use those variables in an econometric analysis of the relationships between sentiment and other variables. We survey this emerging research field and refer to it as sentometrics, which is a portmanteau of sentiment and econometrics. We provide a synthesis of the relevant methodological approaches, illustrate with empirical results, and discuss useful software

An autonomous system designed for automatic detection and rating of film reviews. Extraction and linguistic analysis of sentiments.

International audienceThis paper describes the functions of a system designed for the assessment of movie reviews. Such a system enables the automatic collection, evaluation and rating of film critics' opinions of movies. First the system searches and retrieves probable movie reviews from the Internet, especially those expressed by prolific reviewers. Subsequently the system carries out an evaluation and rating of those movie reviews. Finally the system automatically associates a numerical mark to each review, this is the objective of the system. This data constitutes the input to the cognitive engine. Our system uses three different methods for classifying opinions in critics' reviews. We introduce two new methods based on linguistic knowledge. Results are then compared with the overall statistical method using Bays classifier. The last step is to combine the results obtained in order to make the final assessment as accurately as possible

Components of cultural complexity relating to emotions: A conceptual framework

Many cultural variations in emotions have been documented in previous research, but a general theoretical framework involving cultural sources of these variations is still missing. The main goal of the present study was to determine what components of cultural complexity interact with the emotional experience and behavior of individuals. The proposed framework conceptually distinguishes five main components of cultural complexity relating to emotions: 1) emotion language, 2) conceptual knowledge about emotions, 3) emotion-related values, 4) feelings rules, i.e. norms for subjective experience, and 5) display rules, i.e. norms for emotional expression

Optimizing L2 Vocabulary Acquisition: Applied Linguistic Research

Any acquisition in Second Language Acquisition (SLA) starts as word recognition; as such vocabulary acquisition is integral to language learning as a whole and is a precursor to fluent communication (Ellis, 1996; Moore, 1996). To maximize SLA, vocabulary acquisition must be optimized. However, vocabulary acquisition is understudied and underutilized, especially compared to other aspects of SLA (Paribakht & Wesche, 1997). Cook states, “…the vast bulk of examinations, syllabuses, and course books around the globe show little overt influence from SLA research” (1998, p.10). Courses, teachers, and students would benefit from directly addressing SLA research, rather than utilize inefficient methods (Cook, 1998; Moore, 1996). Problematic course books influence thousands of teachers and a multitude of students (Cook, 1998); this costs educational institutions billions of dollars globally. Prioritizing sound pedagogy when designing courses would alleviate the problems of inefficient acquisition in SLA and the financial cost. An outline is presented for creating and supplementing programs in instructed SLA, these guidelines utilize linguistic research on vocabulary acquisition: 1) The course is built using frequency data, from spoken corpus in the target language. Zipf’s law dictates that word frequency occurs on a predictable curve where the most frequent word is twice as common as the next most frequent word; word rank is inversely proportional to frequency (Milton, 2009). The 100 most frequent words can be up to 50% of a text (Moore, 1996). The 2,000 most frequent words of English make up about 80% of the language. The next 2,000 words are 8% of the occurrences (Milton, 2009). Vocabulary sorting based on frequency, will provide the most useful words and [Document title] will front-load functional words, allowing L2 acquirers to create grammatical constructions (Milton, 2009; Moore, 1996). 2) This frequency determined L2 vocabulary, uses small, alliterated word lists instead of semantic sets. Alliterated word lists and phonological similarity improve L2 vocabulary retention (Hulstijn, 2003; Laufer, 2009). Semantic sets have been shown to create confusion (Hulstijn, 2003; Schmidt & Watanabe, 2001). 3) Pseudo immersion is avoided because it is not effective for L2 acquirers (Schmidt & Watanabe, 2001). Cody (2009) states, ‘immersion’ and incidental learning are often attempted. Although immersion is effective for (multiple) L1 acquisition, post critical-period acquisition is radically different; ‘mere exposure’ will not work (Hyltenstam & Abrahamsson, 2003). Explicit instruction in the student’s native language is encouraged (Atkinson, 1987). Lexical meaning must be taught explicitly and utilizing explicit instruction can double retention rates (Laufer, 2009; Laufer & Hulstijn, 2001). 4) Mnemonic devices, visual and otherwise are utilized. Flipping an image upside creates a unique association with the word, rather than have the learner ‘mediate’ with the L1 representation, which they would otherwise default to (Hulstijn, 2003). Learner generated mnemonics were found useful in Cohen’s 1987 study (Laufer, 2009). Multiple studies have determined that mnemonic devices comparing an L2 with a semantically related L1 word are effective (Hulstijn, 2003)

A Review Study on the Enhancement of Oral Fluency in L2: An Investigation into Processes and Didactics

This paper principally endeavors to grant a thorough understanding of the cognitive and expressive mechanisms perpetually involved in the production of speech. It must be noted that oral fluency has proven to be one of the major skills that almost all EFL learners strive to achieve through conscious mental efforts and constant exposure. Oral fluency is then a cognitive process that requires the learner to use their meta-cognitive skills to both enhance the effectiveness and flow of speech, and simultaneously avoid speech errors

Arabic sentence-level sentiment analysis

Sentiment analysis has recently become one of the growing areas of research related to text mining and natural language processing. The increasing availability of online resources and popularity of rich and fast resources for opinion sharing like news, online review sites and personal blogs, caused several parties such as customers, companies, and governments to start analyzing and exploring these opinions. The main task of sentiment classification is to classify a sentence (i.e. review, blog, comment, news, etc.) as holding an overall positive, negative or neutral sentiment. Most of the current studies related to this topic focus mainly on English texts with very limited resources available for other languages like Arabic, especially for the Egyptian dialect. In this research work, we would like to improve the performance measures of Egyptian dialect sentence-level sentiment analysis by proposing a hybrid approach which combines both the machine learning approach using support vector machines and the semantic orientation approach. Two methodologies were proposed, one for each approach, which were then joined, creating the hybrid proposed approach. The corpus used contains more than 20,000 Egyptian dialect tweets collected from Twitter, from which 4800 manually annotated tweets will be used (1600 positive tweets, 1600 negative tweets and 1600 neutral tweets). We performed several experiments to: 1) compare the results of each approach individually with regards to our case which is dealing with the Egyptian dialect before and after preprocessing; 2) compare the performance of merging both approaches together generating the hybrid approach against the performance of each approach separately; and 3) evaluate the effectiveness of considering negation on the performance of the hybrid approach. The results obtained show significant improvements in terms of the accuracy, precision, recall and F-measure, indicating that our proposed hybrid approach is effective in sentence-level sentiment classification. Also, the results are very promising which encourages continuing in this line of research

Lexical Derivation of the PINT Taxonomy of Goals: Prominence, Inclusiveness, Negativity Prevention, and Tradition

What do people want? Few questions are more fundamental to psychological science than this. Yet, existing taxonomies disagree on both the number and content of goals. We thus adopted a lexical approach and investigated the structure of goal-relevant words from the natural English lexicon. Through an intensive rating process, 1,060 goal-relevant English words were first located. In Studies 1-2, two relatively large and diverse samples (total n = 1,026) rated their commitment to approaching or avoiding these goals. Principal component analyses yielded 4 replicable components: Prominence, Inclusiveness, Negativity prevention, and Tradition (the PINT Taxonomy). Study 3-7 (total n = 1,396) supported the 4-factor structure of an abbreviated scale and found systematic differences in their relationships with past goal-content measures, the Big 5 traits, affect, and need satisfaction. This investigation thus provides a data-driven taxonomy of higher-order goal-content and opens up a wide variety of fascinating lines for future research

Learning new words: Memory reactivation as a mechanism for strengthening and updating a novel word´s meaning

In the present study we explored the post-learning changes in a novel word’s definition using a cue-induced memory reactivation. Native speakers of Spanish (N=373) learned low-frequency words with their corresponding definitions. The following day, reactivated groups were exposed to a reminder and provided a subjective assessment of reactivation for each word, while control groups did not receive a reactivation. Study A demonstrated that memory reactivation enhances both explicit recall and semantic integration of new meanings. Study B investigated the effect of memory reactivation in the modification of the new meanings, through three different experiments. Results show an improvement of the updated definitions according to each word´s reactivation strength. In addition, congruence with previous knowledge was suggested to be a boundary condition, while consolidation time had a positive modulatory effect. Our findings call attention to reactivation as a factor allowing for malleability as well as persistence of long-term memories for words.Fil: Laurino, Julieta. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Forcato, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Tecnológico de Buenos Aires; ArgentinaFil: Coaker, Nicole. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Pedreira, Maria Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Kaczer, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentin

The Effect of Masking the Prime in Orthographic and Semantically Related Pairs : An Interactive Activation Account

Visual word recognition studies rely on priming tasks to examine underlying processes within the lexical system. A commonly used method is the lexical decision task, where participants are presented with a letter string that is either a familiar word or a meaningless non word such as fost. Response times are measured for the time taken to decide if the letter string is a word or a non word. The word the participant responds to is the target, while the preceding word is referred to as the prime. There are three types of priming conditions reported here. First, semantic priming where a target in the pair chair-table is recognised faster than the target in the pair horse-table. Semantic priming studies are considered to reflect later processes in word recognition, which can occur after primes have been identified. A second paradigm is orthographic priming, where the target in a word pair sharing letters, such as fable-table, is recognised faster than the target item in the control pair shoot-table, in which no letters overlap. Orthographic priming appears to be more robust in a masked condition. That is, the prime stimulus is presented so briefly and in close proximity to other visual features that it cannot be readily recognised. The reason targets in orthographically related pairs are more likely to be facilitated when the prime is masked is unresolved. This work addresses this question by examining what effect the mask can have on the processing of the prime. There are two opposing views. Firstly, it is assumed word recognition occurs over time, and when a mask appears shortly after a word has been presented, further processing of the prime immediately ceases. However, because the prime has already been perceived by the system to some degree, it is said to be partially activated. This partial activation can persist for a brief period of time, but later processes of recognition do not occur, and the word is never identified by the lexical system. This is referred to as an interruption theory of masking. The alternate account suggests the mask does not disrupt the processing of the prime, rather, it affects the ability a person has in consciously reporting the primes presence. That is, the word may have been identified by the lexical system, but it has not been identified by the conscious system. Determining the true effect of a mask has proved difficult. There are many parameters within the existing models of word recognition that are yet to be accurately identified and described. With a large volume of data from a vast array of different priming designs, theory testing is likely to remain a slow process. This paper aims to take a unique approach of examining both orthographic and semantic priming within the same design, which are considered here to be somewhat opposing forces. Unexpectedly, no orthographic priming was found in a design previously showing a robust effect. The results are examined in terms of an interactive activation model, where an interruption account of the prime did not appear to be supported. An expected result was obtained however in that a semantic priming effect was not found in the masked condition. Subsequent tests attempted to obtain a semantic effect while looking at the relationship between semantic priming and conscious awareness of the primes. The study highlights some of the difficulties in making an unbiased assessment of the participants ability to detect masked primes