Movie reviews

This paper presents a machine learning-based (ML) approach for identifying
fake news on web-based social media networks. Data was acquired from
Facebook to develop the model which was used to identify Afan Oromo's
false news. The system architecture uses algorithms, such as support vector
machines (SVM), k-nearest neighbor (KNN), and convolutional neural
networks (CNNs) to detect and classify fake news. Existing models have
limitations in understanding reported news accuracy compared with verified news. This study successfully resolved the challenges in the detection of social media fake news detection for the Afan Oromo language with the use of ML models and natural language processing (NLP) techniques. The results show that the SVM approach achieved a precision, recall, and F1-score, of 0.92, 0.92, and 0.90.

Sentiment analysis is a review analysis process used to determine whether an opinion is neutral, negative, or positive. Sentiment analysis can be done using lexicon-based or machine learning-based approaches. Lexicon can perform sentiment analysis without training data because it is dictionary-based but performs worse than machine learning. Machine learning can perform well in completing sentiment analysis but requires training data so that the model does not experience underfitting. In the case of sentiment analysis on big data, manual labeling of training data is an inefficient job. Support vector machine (SVM) has the opportunity to be used together with the active learning (AL) method to make small training data but still have good performance. This research proposed a hybrid lexicon and AL-SVM method to complete sentiment analysis on big data tourism. This research used polarity from the valence aware dictionary and sentiment reasoner (VADER) lexicon as a reference for the query by user process from the AL-SVM to automate the sentiment analysis process on big data. The experimental results showed that using the hybrid lexicon and AL-SVM increased the sentiment analysis performance compared to the VADER lexicon, SVM, and lexicon SVM, which run separately.

The Imaginative Conservative, July 16, 2024. Despite making fun of the nature of tech company perfidy and internet culture, "The Mitchells vs. The Machines," like too many animated films, may simply add to the inability of its younger viewers to follow a story for more than a minute.

Sentiment analysis is a method of analyzing data to identify its intent. It
identifies the emotional tone of a text body. Aspect-based sentiment analysis
is a text analysis technique that identifies the aspect and the sentiment
associated with each aspect. Different organizations use aspect-based
sentiment analysis to analyze opinions about a product, service, or idea.
Traditional sentiment analysis methods analyze the complete text and assign
a single sentiment label to it. They do not handle the tasks of aspect
association, dealing with multiple aspects and inclusion of linguistic
concepts together as a system. In this article, AlgoDM, an algorithm to
perform aspect-based sentiment analysis is proposed. AlgoDM uses a novel
concept of IDistance matrix to extract aspects, associate aspects with
sentiment words, and determine the sentiment associated with each aspect.
The IDistance matrix is constructed to calculate the distance between aspects
and the words expressing the sentiment related to the aspect. It works at the
sentence level and identifies the opinion expressed on each aspect appearing
in the sentence. It also evaluates the overall sentiment expressed in the
sentence. The proposed algorithm can perform sentiment analysis of any
opinionated text.

and founding co-editor of Markets, Globalization and Development Review. Dr. Dholakia's research deals with globalization, technology, innovation, market processes, and consumer culture. His current work focuses on global social aspects of new media and sentient technologies such as robotics and autonomous vehicles. Deniz Atik is Assistant Professor of Marketing, University of Texas Rio Grande Valley (UTRGV), and founding co-editor of Markets, Globalization & Development Review. Dr. Atik's research interest focuses on transformative consumer research and macromarketing, specifically theories of fashion, sustainability and vulnerable consumers. She has been contributing to well-recognized academic marketing journals with her academic work, and teaching marketing and consumer culture related courses in USA,

In recent years various attempts have been made to automatically mine opinions and sentiments from natural language in online networking messages, news, and product review businesses. Sentiment analysis is needed as an effort to improve service performance in the organization. In this paper, we have explored the polarization of positive and negative sentiments using Twitter user reviews. Sentiment analysis is carried out using the Naïve Bayes (NB), support vector machine (SVM), and logistic regression (LR) model then compares the results of these three models. The results of the experiment showed that the accuracy of LR was better than SVM and NB, namely 77%, 76%, and 70%.

New applications of text categorization methods like opinion mining and sentiment analysis, author profiling and plagiarism detection requires more elaborated and effective document representation models than classical Information Retrieval approaches like the Bag of Words representation. In this context, word representation models in general and vector-based word representations in particular have gained increasing interest to overcome or alleviate some of the limitations that Bag of Words-based representations exhibit. In this article, we analyze the use of several vector-based word representations in a sentiment analysis task with movie reviews. Experimental results show the effectiveness of some vector-based word representations in comparison to standard Bag of Words representations. In particular, the Second Order Attributes representation seems to be very robust and effective because independently the classifier used with, the results are good.

It's always great to be introduced to new, young talent coming out of a sister nation like Iran. I'd interviewed you previously in a roundtable discussion on Farsi SFF but here's a chance to do a more personalized, in-depth tit-for-tat. And thanks for providing me with samples of your work-The Design Agency, The Unholy, in addition to some of your short stories. Interview conducted by Emad Aysha First of all let me commend you on your English, and your taste for pinching satire, which is also very Englishy. Where we you schooled in English?

It was a dark and stormy night when five friends decided to explore an abandoned house on the outskirts of town. The house had been vacant for years, and it was rumored to be haunted by the ghosts of the previous owners. The friends, being thrill-seekers, were excited to investigate. As they approached the house, they could see that it was in a state of disrepair. The windows were boarded up, and the front door hung off its hinges. The friends hesitated for a moment before pushing the door open and stepping inside.

This study aims to identify the social inequalities depicted in the film Parasite. This study uses Roland Barthes' semiotic analysis method. The supporting data for this study use a literature review to obtain relevant theories and data that can be used to solve the problem. The results showed that, in representation and implication, parasite films have social inequality implications, indicated by multiple markers in the form of audio and images. Forms of social inequality, such as inequality in education, inequality in living conditions, and inequality in opportunity. Peripheral myths such as the myth of education fever and the three treasures generation. On the other hand, the ideology that surrounds it is that of individualism fed by the capitalist economic system.

The Internet has facilitated the growth of recommendation system owing to the ease of sharing customer experiences online. It is a challenging task to summarize and streamline the online textual reviews. In this paper, we propose a new framework called Fuzzy based contextual recommendation system. For classification of customer reviews we extract the information from the reviews based on the context given by users. We use text mining techniques to tag the review and extract context. Then we find out the relationship between the contexts from the ontological database. We incorporate fuzzy based semantic analyzer to find the relationship between the review and the context when they are not found therein. The sentence based classification predicts the relevant reviews, whereas the fuzzy based context method predicts the relevant instances among the relevant reviews. Textual analysis is carried out with the combination of association rules and ontology mining. The relationship between r...

A rediscovered Italian movie (1953), which is both a WIP (Women In Prison) example, and an unexpected feminist burst. A couple of times after, the story (from a French novel of Léon Gozlan), has come to the screen again, always as Italian production, with the story changed to a different sensitivity about women in modern society. With "classic" topics about women's attitudes, as Hollywood and the movie industries dictate.

BY RON BLUM AND MIKE STARRELS Beginning with the FallQuar-EVALUATION" suggests some ter in September, 1969, classes further innovations for Jefferson. Wide spread dissatisfaction at Jefferson will begin at 9 A.M. About 7 4 percent ofthose-answer-with the testing and evaluation rather than at the 8 A.M. hour. ing favored the institution of an system at Jefferson is evident This action is a direct result of "Exam Week" in the basic by 85 percent of the students the data pro •d d by h s d indicating reservation with or v1 e t e tu ent science years. This implies a Council Curriculum Evaluation period of timeduringwhichregu-outright rejection of the present C om mitt e e (SCCEC) Student lar classes are suspended, al-system. Of tho s e rejecting the • Opinion Poll, presented else-lowing an equal distribution of present methods, ther e we re where in this issue of ARIEL e~aminations with no intermittent twice as many juniors as freshcoupled with active facu1ty sup~ scheduled activity. Opinions on • men and sophomores. This data port. The Pollshowedthatslight-"METHOD OF GRADING" indi-may reflectdifferentexperiences ly Over On th. d f h d and opportunities ava1•1able to eir o t e stu enl cated a two-to-one mar gin in body was satisfied with the 8 A.M. favor of changing the present juniors. Why does it appear that starting hour, while the rest 0: numerical system to a pas s-fail as a student gets closer to clinithe respondents • d • t d h • .cal practice there 1• s i •ncreased m ica e t eu system. Subjective comment on dissatisfaction by noting pref-thi s que stion strongly favore' d a rejection bf Jeffe:r-son' s testing erences for an 8:30 or 9 A.M. st r ict pass-fail system, i.e. only methods? starting time. This change will t hose two designations would be ~tudents also freely comnot affes:t the c;:linical rotations of used, rather than high pass, pass, mented on questions relative to the junior and. senior clas ses. low pas s or some otherfraction-the NationalBoardExaminations. Establishing advisors for the ization. The method of examina-It should be noted that the refour year s was supported by about tion at Jefferson also came under sponses of the first and second 78 percent of tho se people ans-scrutiny. While 10 percent of the year students represent opinions weiing the Poll. This has result-respondents preferredjusttaking and attitudes acquired in and out , ed in Dr. Kellow' s recent appoint-a final examination in each of class, while those of juniors ment ~f a smdent-facul~y ad hoc ,, course, by far the majority, or. add the experience of having Comm.1ttee on .counseling. The 65 percent, favored both mid-taken the examination. An aver-comm1ttee consists of three stu-term and final examinations. The age oi about 56 percent felt that dent~ and three faculty members, significant precentage (Z 5 %) se-the National Board Examinations and is to submit a report to the lecting "other" mayindicatethat are overemphasized intheteach-Dean tn tt~oae >tn ..

The Imaginative Conservative, August 20, 2021.  I cannot fully accept the world of John Wick. But like the pagan world and the Old Testament's eye-for-an-eye, I cannot fully reject it either. The world of Wick is a world of senseless violence and also violence that is roughly sensible because it is informed by justice.

Violence is an act of physical force that causes or is intended to cause harm. The damage inflicted by violence may be physical, psychological, or both.or both. Violence may be distinguished from aggression, a more general type of hostile behaviour that may be physical, verbal, or passive in nature.Media violence is recognized as a potential contributor to the increase of antisocial attitudes in children and adolescents today. The relationship between heavy exposure to media violence and later aggressive behavior has been studied for more than thirty years. A large body of experimental and longitudinal research on this question has been evaluated, and it has been determined that there is a link between viewing TV violence and aggressive behavior. This review article focuses on the adverse effect of violence movie on humans especially children, types of violence, causes of violence, effects of violence, prevention of violence, role of media to create a perception and the short-term effects of violence movies on human behaviour. This article indicates a positive association between movies violence and aggressive attitudes. The preponderance of evidence from many research studies over the years shows that the violence portrayed on media influences the attitudes and behaviour of humans especially children who watch it. Media violence is one of the things that may lead to aggressive, antisocial, or criminal attitudes; it does, however, usually work in association with other factors.Because the tendency to behave violently develops during childhood after some exposure to violence movies, it will be essential for regulations of the program to set in coupled with parental controls, this will help limit the damages violent movies could cause.

and founding co-editor of Markets, Globalization and Development Review. Dr. Dholakia's research deals with globalization, technology, innovation, market processes, and consumer culture. His current work focuses on global social aspects of new media and sentient technologies such as robotics and autonomous vehicles. Deniz Atik is Assistant Professor of Marketing, University of Texas Rio Grande Valley (UTRGV), and founding co-editor of Markets, Globalization & Development Review. Dr. Atik's research interest focuses on transformative consumer research and macromarketing, specifically theories of fashion, sustainability and vulnerable consumers. She has been contributing to well-recognized academic marketing journals with her academic work, and teaching marketing and consumer culture related courses in USA,

The Internet has facilitated the growth of recommendation system owing to the ease of sharing customer experiences online. It is a challenging task to summarize and streamline the online textual reviews. In this paper, we propose a new framework called Fuzzy based contextual recommendation system. For classification of customer reviews we extract the information from the reviews based on the context given by users. We use text mining techniques to tag the review and extract context. Then we find out the relationship between the contexts from the ontological database. We incorporate fuzzy based semantic analyzer to find the relationship between the review and the context when they are not found therein. The sentence based classification predicts the relevant reviews, whereas the fuzzy based context method predicts the relevant instances among the relevant reviews. Textual analysis is carried out with the combination of association rules and ontology mining. The relationship between r...

Currently, sentiment analysis into positive or negative getting more attention from the researchers. With the rapid development of the internet and social media have made people express their views and opinion publicly. Analyzing the sentiment in people views and opinion impact many fields such as services and productions that companies offer. Movie reviewer needs many processing to be prepared to detect emotion, classify them and achieve high accuracy. The difficulties arise due of the structure and grammar of the language and manage the dictionary. We present a system that assigns scores indicating positive or negative opinion to each distinct entity in the text corpus. Propose an innovative formula to compute the polarity score for each word occurring in the text and find it in positive dictionary or negative dictionary we have to remove it from text. After classification, the words are stored in a list that will be used to calculate the accuracy. The results reveal that the syst...

Esta tese objetivou investigar a relacao da narrativa brasileira contemporânea e os temas que a ela se vinculam, em especial a transexualidade e a configuracao do duplo, a partir da analise da protagonista transexual e narradora Cleopatra, do romance Do fundo do poco se ve a lua (2010), do brasileiro Joca Reiners Terron (1968-). A partir desse objetivo e atraves de perspectivas historicas da literatura de cunho homoerotico, ratificamos a importância social da tematica na narrativa analisada atuando como proponente de novos dialogos sobre a identidade transexual na sociedade brasileira. Ademais, discutimos o processo cirurgico de redesignacao sexual, submetido pelo personagem Wilson, o qual se transmudou para a personagem Cleopatra. Essas nuances ressaltaram como as minorias representadas por Cleopatra enfrentam a constante negacao sociocultural e identitaria no Brasil. Apoiamo-nos nos estudos de Bento (2006, 2008, 2012, 2017) para confirmar essa condicao no âmbito real. O duplo pres...

The present paper aims to study the animation movie scriptwriter’s intention of using flouting of maxims as a way to create an entertaining animated movie Kung Fu Panda 1. The present study is a work, directed by Grice’s theory of Implicature and built upon its main principle (The Cooperative Principle, which contains four maxims: Quantity, Quality, Relation, and Manner) and tries to show how flouting of maxims can add to the thematic and entertainment value of the movie. The paper shows how flouting of maxims can be beneficial in making an entertaining movie and why the scriptwriters use flouting of the maxim in their movies. Select dialogues have been chosen from the script of Kung Fu Panda movie for the analysis of flouting of maxims. The paper includes four sections: The first section deals with the introduction which states cooperative principle, conversational maxims, flouting maxims and conversation. The second section presents an overview of the selected animated movie and the criteria for selection of data. The third section contains the methodology used for analyzing and interpreting selected data. The fourth section shows the result of the present study and shows how flouting of maxims is essential to the interlocutors and attracts the audience’s attention.

W niniejszym tekście przedstawione są wyniki badania pilotażowego na temat niezbyt jeszcze zbadany: czynników odpowiedzialnych za to, że recenzje fi lmowe są oceniane pozytywnie przez odbiorców. Jest to problem istotny z co najmniej dwóch powodów. Po pierwsze, jest on mało zgłębiony mimo rosnącej od kilku lat liczby badań recenzji. Po drugie, recenzje różnego rodzaju stają się coraz istotniejsze dla odbiorców, zwłaszcza wobec coraz większej liczby produkcji fi lmowych i zmiany modelu odbioru fi lmów-przesuwającego się ku różnym formom dostępu online na żądanie. Coraz większy udział w rynku uzyskują serwisy i usługi oferujące zarówno produkcje własne, jak i fi lmy obce. W związku z tym rośnie też zainteresowanie wstępną selekcją zwiększającej się oferty fi lmowej. Badanie recenzji ma też szersze perspektywy, ponieważ są one wycinkiem o wiele obszerniejszego zjawiska recenzowania i opiniowania różnych produkcji (spektakle, gry…), usług i towarów.

The article is a brief insight into the movie 'Oleg' by the Lithuanian director Juris Kursietis presented at the 2019 online edition of the GoEast Film Festival.  The film's main character is an ethnic Russian butcher living
in Riga (Valentin Novopolskij), with a non-citizen passport, going to Belgium to work in a meat factory. He will eventually face several obstacles and difficulties in terms of professional and cultural integration ending up coming close to criminality.

U Zagrebu je 14. prosinca prošle godine u kinu Kaptol Boutique Cinema održana hrvatska premijera dugometražnoga dokumentarnog filma Zidine o logorima za Hrvate u BiH tijekom rata 90-ih godina. Događaj je održan u organizaciji i pod pokroviteljstvom Hrvatskog sabora. Riječ je o filmu koji traje oko sto minuta, sadrži mnoštvo arhivskih snimaka te kroz razgovor sudionika prikazuje situaciju u logorima u vrijeme rata, ali i njihova sjećanja godinama nakon rata. Scenarist filma je Ivo Čolak, koji ujedno potpisuje režiju u suradnji s Markom Mikulićem. Produkciju filma potpisuje tvrtka SIMBOL (za Hrvatsku udrugu logoraša Domovinskog rata u BiH).

One of the methods used in detecting the intrusion detection system is by implementing Naïve Bayes algorithm. However, Naïve Bayes has a problem when one of the probabilities is 0, it will cause inaccurate prediction, or even no prediction was found. This paper proposed two modifications for Naïve Bayes algorithm. The first modification eliminated the variable that has 0 probability and the second modification changed the multiplication operations to addition operations. This modification is only applied when the Naïve Bayes algorithm does not find any prediction results caused by zero probabilities. The results of this research show that the value of precision, recall, and accuracy in the modification made tends to increase and better than the original Naïve Bayes algorithm. The highest precision, recall, and accuracy are obtained from modification by changing the multiplication operation to the addition. Increasing precision can reach 4%, increasing recall reaches 2% and increasin...

Currently, sentiment analysis into positive or negative getting more attention from the researchers. With the rapid development of the internet and social media have made people express their views and opinion publicly. Analyzing the sentiment in people views and opinion impact many fields such as services and productions that companies offer. Movie reviewer needs many processing to be prepared to detect emotion, classify them and achieve high accuracy. The difficulties arise due of the structure and grammar of the language and manage the dictionary. We present a system that assigns scores indicating positive or negative opinion to each distinct entity in the text corpus. Propose an innovative formula to compute the polarity score for each word occurring in the text and find it in positive dictionary or negative dictionary we have to remove it from text. After classification, the words are stored in a list that will be used to calculate the accuracy. The results reveal that the syst...

The Spy Gone North (Gongjak). Plotted less as spy story and more as political exposé. based on the true story of a South Korean intelligence operative, code-named Black Venus, who infiltrated and corrupted North Korean power circles during the nuclear crisis of the 1990s. The subject will certainly be its selling point outside Asia, though the first half will need disentangling for non-Korean audiences. Clocking in at almost two and a half hours, the story initially races along so fast and with so many historical facts to absorb that one wishes it would slow down. Typed titles on the screen inform that after the Korean War (1950-'53), an armistice was signed between the two countries. The South became rich and capitalist and the North continued poor and communist under supreme leader Kim Jong-il.

An increase in use of web produces large content of information about products. Online reviews are used to make decision by peoples. Opinion mining is vast research area in which different types of reviews are analyzed. Several issues are existing in this area. Domain adaptation is emerging issue in opinion mining. Labling of data for every domain is time consuming and costly task. Hence the need arises for model that train one domain and applied it on other domain reducing cost aswell as time. This is called domain adaptation which is addressed in this paper. Using maximum entropy and clustering technique source domains data is trained. Trained data from source domain is applied on target data to labeling purpose A result shows moderate accuracy for 5 fold cross validation and combination of source domains for Blitzer et al (2007) multi domain product dataset.

She received her J.D. (magna cum laude) and LL.M. in Admiralty (with distinction) from Tulane Law School. She currently teaches in the areas of Civil Procedure, Conflict of Laws, Federal Jurisdiction, Admiralty & Maritime Law, and Popular Culture & the Law. She would like to express her gratitude to Dean Leticia M. Diaz for her continuing support of faculty scholarship and the research grant that assisted in the writing of this article. Prior to beginning her legal studies, Professor Simpson-Wood was a professional actress for a number of years. She is a long-time member of the Actors' Equity Association and Screen Actors Guild & the American Federation of Radio and Television Artists. Full disclosure: Professor Simpson-Wood is a die-hard New Orleans Saints fan.

An assessed hotel service is necessary for tourists and everyone who is traveling, however currently it is still difficult to find recommended hotel information. The solution provided in this research is to propose a smart application that has been developed by implementing machine learning in it. The purpose is to build a sentiment review smart application by applying the sentiment analysis hybrid model of the best neural network (NN) algorithm model that has been optimized using genetic algorithms. To get the right model, the research method was carried out with experiments starting from the initial stages of conducting data preprocessing, tokenization, weighting, modeling experiments, and conducting the system evaluation stage to determine the success of the proposed model. The progress of the application development system is by using the prototyping model. SentiHotel is a sentiment application that was successfully built to provide a solution for tourists in assessing a hotel s...

One of the methods used in detecting the intrusion detection system is by implementing Naïve Bayes algorithm. However, Naïve Bayes has a problem when one of the probabilities is 0, it will cause inaccurate prediction, or even no prediction was found. This paper proposed two modifications for Naïve Bayes algorithm. The first modification eliminated the variable that has 0 probability and the second modification changed the multiplication operations to addition operations. This modification is only applied when the Naïve Bayes algorithm does not find any prediction results caused by zero probabilities. The results of this research show that the value of precision, recall, and accuracy in the modification made tends to increase and better than the original Naïve Bayes algorithm. The highest precision, recall, and accuracy are obtained from modification by changing the multiplication operation to the addition. Increasing precision can reach 4%, increasing recall reaches 2% and increasing accuracy reaches 2%.

Bag-of-words approach is popularly used for Sentiment analysis. It maps the terms in the reviews to term-document vectors and thus disrupts the syntactic structure of sentences in the reviews. Association among the terms or the semantic structure of sentences is also not preserved. This research work focuses on classifying the sentiments by considering the syntactic and semantic structure of the sentences in the review. To improve accuracy, sentiment classifiers based on relative frequency, average frequency and term frequency inverse document frequency were proposed. To handle terms with apostrophe, preprocessing techniques were extended. To focus on opinionated contents, subjectivity extraction was performed at phrase level. Experiments were performed on Pang & Lees, Kaggle's and UCI's dataset. Classifiers were also evaluated on the UCI's Product and Restaurant dataset. Sentiment Classification accuracy improved from 67.9% for a comparable term weighing technique, DeltaTFIDF, up to 77.2% for proposed classifiers. Inception of the proposed concept based approach, subjectivity extraction and extensions to preprocessing techniques, improved the accuracy to 93.9%.

The film has a different structure than the other films. It is made up of six stories. The stories show different problems from everyday life. The objective of the film is to make the viewer reflect and make him feel identified with some of the conflicts that the film presents. Wild Tales is a film that takes different conflict situations from everyday life and takes them to the most extreme. This makes us reflect on how such a common situation in daily life can turn into something disastrous and violent, which can even destroy us and end our lives, if we allow ourselves to be carried away by our impulses and desires. The characters in each story awaken the wild behavior of the human being by being subjected to unfair and abusive situations, this makes them lose the control so they let themselves be guided by their impulses and desires for revenge, and this leads them to a violent destiny. Plot The movie shows six different stories. The stories show different conflictive situations of daily life, where the characters always lose control which leads them to a crazy and catastrophic end. The stories are self-conclusive and they are all linked by a common theme which is the violence. About the movie Wild Tales is a Spanish-Argentine film written and directed by Damián Szifron. The film was released in 2014 and received numerous awards. Stories and characters Pasternack: Darío Grandinetti, as Salgado., María Marull, as Isabel., Mónica Villa, as Professor Leguizamón and Diego Starosta, as Ignacio Fontana. The rats: Julieta Zylberberg, as the girl, Rita Cortese, as the cook, César Bordón, as Cuenca and Juan Santiago Linari, as Alexis. The strongest: Leonardo Sbaraglia as Diego Iturralde and Walter Donadoas Mario. Little bomb: Ricardo Darín as Simón Fisher., Nancy Dupláa as Victoria., Luis Mazzeo as Colleague., Pablo Moseinco as Lawyer. and Alfonso Grispino as Father-in-law. The proposal:. Oscar Martínez as Mauricio, María Onetto as Helena, Osmar Núñez as the lawyer, Germán de Silva as José, the landlord, Diego Velázquez as the prosecutor, and Alan Daicz as Santiago. Until death do us parts: Érica Rivas as Romina., Diego Gentile as Ariel., Liliana Weimer as Cuca., Paula Grinszpan as Amiga. and Gustavo Bonfigli as DJ.

The director in charge of the photography and the shots in the film was Jim Van Dijk and Neal Seale, who used various styles of photography, among which the extreme long shot, medium long shot, long shot, close up shot and among others stand out.

Delete (System Meltdown) Movie Analysis Delete is a movie about how our technology is a huge help for us but also a danger to humans. A Virus was sent to the Military database and at first they thought it was hackers who are targeting them but they didn't know that it was an artificial intelligence that can actually have its own thoughts. Daniel Gerson a PC nerd infers that what they are managing with is The Singularity, a man-made Ai that has become rogue on the web and can influence any associated framework. As they attempt to discover a methods for deleting it, the A.I. exhibits startling capacities to follow them, feed false information, issue capture warrants and copy cellphone brings in its endeavors to divert them from opening a drive that contains data. At the same time, the A.I. causing worldwide disarray by closing down basic PC frameworks. As mayhem rules over the globe, it becomes evident that man-made Ai has transformed into a dangerous thing with the sole motivation behind its purpose to bring catastrophe. With humanity confronting annihilation, the best way to spare the world is to make a second type of man-made consciousness that is similarly as alive, similarly as keen and similarly as risky. While the American government thrashes away helplessly and they can't do nothing, the protagonist go off grid to attempt to stop it. For me this movie is not good because of the low budget they have and also the main story is just plain boring. But I got to give props to the director for putting a lot of accurate stuff in the movie for example is how the Computer geek explains hacking in a beginner level in order for the viewers to understand. But the story is linear and predictable, this goes to show how technology can really affect how people live and it can also cause mayhem through the process. Globalization has to be a key part on this movie because the technology they are fighting with is an ai with control over different components around the world this is to show that technology has come a long way from just a simple machine, to a complex one. And I think that the movie shows the strong points in how the government approach professionals in that field to help them resolve the matter since they have no idea how to fight it. It said there that our fragile digital world will also be our doom. My recommendation for this movie is I hope they focused more on the acting because the emotions are not seen in the actors and they focused more on the cheap effects