Crime scripting: A systematic review

The file attached to this record is the author's final peer reviewed version.More than two decades after the publication of Cornish’s seminal work about the script-theoretic approach to crime analysis, this article examines how the concept has been applied in our community. The study provides evidence confirming that the approach is increasingly popular; and takes stock of crime scripting practices through a systematic review of over one hundred scripts published between 1994 and 2018. The results offer the first comprehensive picture of this approach, and highlights new directions for those interested in using data from cyber-systems and the Internet of Things to develop effective situational crime prevention measures

Sentiment Analysis Based on Deep Learning: A Comparative Study

The study of public opinion can provide us with valuable information. The analysis of sentiment on social networks, such as Twitter or Facebook, has become a powerful means of learning about the users' opinions and has a wide range of applications. However, the efficiency and accuracy of sentiment analysis is being hindered by the challenges encountered in natural language processing (NLP). In recent years, it has been demonstrated that deep learning models are a promising solution to the challenges of NLP. This paper reviews the latest studies that have employed deep learning to solve sentiment analysis problems, such as sentiment polarity. Models using term frequency-inverse document frequency (TF-IDF) and word embedding have been applied to a series of datasets. Finally, a comparative study has been conducted on the experimental results obtained for the different models and input feature

A decision support system framework to track consumer sentiments in social media

With the evolution of web 2.0 and social networks, customers and companies’ online interaction is growing at a fast pace, containing valuable insights about consumers’ expectations that should be monitored and explored in a day-to-day basis. However, such information is highly unstructured and difficult to analyze. There is an urgent need to set up transparent methods and processes to integrate such information in the tourism industry technological infrastructure, especially for small firms that are unable to pay for expensive services to monitor their online reputation. The current paper uses a text mining and sentimental analysis technique to structure online reviews and present them on a decision support system with two different dashboards to assist in decision-making. Such system may help managers develop new insights and strategies aligned with consumers’ expectations in a much more flexible and sustainable pace.info:eu-repo/semantics/acceptedVersio

Analyzing the drivers of customer satisfaction via social media

Social media became a great influence force during the last decade. Active social media user population increased with the new generations. Thus, data started to accumulate in tremendous amounts. Data accumulated through social media offers an opportunity to reach valuable insights and support business decisions. The aim of this project is to understand the drivers of customer satisfaction by public sentiments on Twitter towards a financial institution. Data was extracted from the most popular microblogging platform Twitter and sentiment analysis was performed. The unstructured data was classified by their sentiments with a lexicon-based model and a machine learning based model. The outcome of this study showed machine learning based model successfully overcame the language specific problems and was able to make better predictions where lexicon-based model struggled. Further analysis was performed on the extreme daily average sentiment scores to match these days with prominent events. The results showed that the public sentiment on Twitter is driven by three main themes; complaints related to services, advertisement campaigns, and influencers’ impact.Sosyal medyanın etki alanı geçtiğimiz yıllarla birlikte giderek artmıştır. Yeni jenerasyonlarla birlikte aktif olarak sosyal medya kullanan nüfus artış göstermiştir. Bu sebeple büyük veri birikimi artmıştır. Sosyal medya üzerinden oluşan büyük veri şirketlerin iş yapış şekillerine yönelik değerli kavrayış ve karar alma mekanizmalarına destek fırsatları sunmaktadır. Bu çalışmanın amacı bir finansal kurumun müşterilerinin memnuniyet seviyelerini sosyal medyada oluşan algıyı kullanarak anlamaya çalışmaktır. Çalışma kapsamında kullanılan veri popüler mikro-blog sitesi Twitter üzerinden derlenmiştir. Yapılandırılmamış bu veri sözlük tabanlı ve makine öğrenmesi tabanlı iki model kullanılarak analiz edilmiştir. Çalışma sonucu makine öğrenmesi tabanlı modelin sözlük tabanlı modelin karşılaştığı Türkçe kaynaklı sorunlardan daha az etkilendiği ve daha başarılı tahminler üretebildiğini göstermiştir. Analizin sonraki aşamasında ortalama sonucu aşırı uçlarda çıkan günler aynı günlerde ortaya çıkan olaylar ile eşleştirilmiştir. Ortaya çıkan sonuçlara göre müşteri memnuniyeti sosyal medyada ortaya çıkan üç temel faktörden etkilenmektedir. Bunlar, şikâyet yönetimi, kampanya yönetimi ve sosyal medya fenomenlerinin etkisi olarak tanımlanmaktadır

Managerial Responses to Online Reviews:A Text Analytics Approach

The study tests the effects of online managerial responses and returning customers' future satisfaction (measured as review ratings) by performing social media text analytics on a hotelsample. Essentially, this article provides insight into meaningful differences in future ratings between responding and non-responding hotels, as well as differences in response stylesbetween ratings improvement and non-improvement. The results indicate that: 1) subsequent ratings are higher if customers receive responses to their previous online reviews; 2) increase in ratings is more significant among low-satisfaction customers, and a decrease in ratings is mitigated if responses are provided; 3) responding to loyal customers – those who have visited and rated the same hotel more than three times – has a limited impact on ratings; 4) responses are longer and sentiment is slightly lower in scenarios where subsequent ratings are improved, but there is no significant difference in the effect of response speed between the two groups; 5) changes in ratings also affect styles of responding to current reviews – if customer satisfaction has improved, response length tends to be shorter and sentiment level tends to be higher. The findings offer both theoretical and managerial implications by demonstrating the utility of social media text analytics

Dimensions of football stadium and museum tour experiences: The case of Europe’s most valuable brands

In the context of football’s globalisation, some of the most important football clubs (FCs) can currently be classified as ‘entertainment multinationals’. Sport hospitality provides opportunities to maximise club stadiums’ use so that they can increase clubs’ annual turnover and function as branding platforms. This study sought to identify the main narratives shared online about—and the dimensions of—visitors’ experiences with top football brands in stadium tours. The data collected for this research comprised 400 text reviews for 10 European FCs’ stadiums (i.e., 4000 reviews) written by visitors in the post-experience phase. Content analysis of these Web reviews was conducted using Leximancer software. The results confirm the existence of 15 themes: fan, tour, stadium, team, museum, room, staff, game, (best) place, ticket, seating, recommend(ation), food, shop and attraction. Most researchers have examined stadium tours from a supply-side perspective. The present study’s aim was, therefore, to contribute to the existing literature by analysing stadium tours’ dimensions from the visitors’ point of view. Stadium tours and museum visits are important sources of revenue that contribute to FCs’ economic sustainability. Offering outstanding customer experiences is thus of utmost importance to maximise club stadiums’ usage and strengthen fans’ engagement.info:eu-repo/semantics/publishedVersio

Sentiment analysis of COVID-19 cases in Greece using Twitter data.

Syndromic surveillance with the use of Internet data has been used to track and forecast epidemics for the last two decades, using different sources from social media to search engine records. More recently, studies have addressed how the World Wide Web could be used as a valuable source for analysing the reactions of the public to outbreaks and revealing emotions and sentiment impact from certain events, notably that of pandemics. Objective: The objective of this research is to evaluate the capability of Twitter messages (tweets) in estimating the sentiment impact of COVID-19 cases in Greece in real time as related to cases. Methods: 153,528 tweets were gathered from 18,730 Twitter users totalling 2,840,024 words for exactly one year and were examined towards two sentimental lexicons: one in English language translated into Greek (using the Vader library) and one in Greek. We then used the specific sentimental ranking included in these lexicons to track i) the positive and negative impact of COVID-19 and ii) six types of sentiments: Surprise, Disgust, Anger, Happiness, Fear and Sadness and iii) the correlations between real cases of COVID-19 and sentiments and correlations between sentiments and the volume of data. Results: Surprise (25.32%) mainly and secondly Disgust (19.88%) were found to be the prevailing sentiments of COVID-19. The correlation coefficient (R2 ) for the Vader lexicon is &#8722; 0.07454 related to cases and &#8722; 0.,70668 to the tweets, while the other lexicon had 0.167387 and &#8722; 0.93095 respectively, all measured at significance level of p < 0.01. Evidence shows that the sentiment does not correlate with the spread of COVID-19, possibly since the interest in COVID-19 declined after a certain time

A Business of Prestige and Profit : Creative Scotland and Contemporary Scottish Film Industry

Tämän tutkielman tavoitteena on selvittää miten prestiisi ja voiton tavoittelu kietoutuvat toisiinsa skotlantilaisessa elokuvateollisuudessa ja erityisesti julkisen rahoituksen varassa toimivan kulttuuriteollisuuden instituution, Creative Scotlandin, toiminnassa. Tämän lisäksi tutkielmassa selvitetään mahdollisia syitä sille, miksi Skotlannin naapurimaat ja Iso-Britannian muut alueet houkuttelevat ulkomaisia elokuvaprojekteja luokseen huomattavasti Skotlantia enemmän, syitä skotlantilaisten elokuvatyöntekijöiden maastamuuttoon ja alan rahoituksen vähyyteen. Lisäksi huomiota kiinnitetään kotoperäisen- ja kansainvälisen tuotannon välisiin suhteisiin ja ulkomaisen investoinnin merkitykseen skotlantilaiselle elokuvateollisuudelle. Tutkimusaineistona on käytetty pääasiassa Creative Scotlandin omia julkaisuja: markkinointimateriaalia, vuosittaisia suunnitelmia ja tilinpäätöksiä vuodesta 2014 vuoteen 2024. Aineistoa tutkitaan kvalitatiivisen kulttuurintutkimuksen ja elokuvatutkimuksen teorian keinoin, eli analysoidaan tutkimusaineistosta nousevia diskursseja ja sidotaan nämä kulttuurisiin konteksteihin. Apuna käytetään akateemista elokuvakirjallisuutta, kulttuurintutkimuksen teoriaa, sekä kulttuuriteollisuuden toimintaa ja merkitystä selittävää teoriaa. Tämän lisäksi kulttuurialan toimittajien kirjoittamat artikkelit toimivat Creative Scotlandin sisäisiä menettelytapoja kriittisesti tarkastelevina lähteinä. Skotlantilainen elokuva koki ensimmäisen kasvukautensa 90-luvun puolivälissä, uusien rahoitusmenetelmien mahdollistaessa ilmapiirin, jossa kotoperäisten elokuvien tuotanto kukoisti ja ennennäkemätön kansallisylpeys elokuvan saralla oli aistittavissa. Elokuvien rahoitukseen ja tuotantoon panostettiin kuitenkin verrattain vähän: verovaroja ohjattiin riittämättömästi julkiseen kulttuurintuotantoon ja muutkin rahoitusmahdollisuudet olivat rajallisia sekä julkisella, että yksityisellä sektorilla. Skotlantilainen kulttuuriteollisuus ja siihen liittyvä politiikka on kuitenkin kehittynyt viime vuosikymmeninä elokuvatuotantoa arvostavampaan ja tukevampaan suuntaan. Elokuvallinen representaatio on kansakunnan identiteetille merkittävä, sillä elokuvallisen ilmaisun kautta katsojaa voidaan puhutella uniikilla tavalla. Skotlantilaisten elokuvantekijöiden lähtökohdat ja tavoitteet elokuvilleen ovat moninaisia, ja tämän vuoksi Creative Scotland on sitoutunut tukemaan niin taide-elokuvaa, sosiaalista realismia kuvaavaa elokuvaa kuin taloudellisesti kannattavaa viihde-elokuvaakin. Creative Scotlandin yksi merkittävimmistä haasteista on tasapainon löytäminen rahoituksen jakamisessa kotimaisille ja ulkomaisille tuotantoyhtiöille ja elokuvantekijöille, sillä monimuotoiset elokuvan tekemisen tavat tuovat oman arvonsa skotlantilaiselle elokuvateollisuudelle lisääntyvän prestiisin tai taloudellisen kasvun kautta. Kansainvälisen arvostuksen saavuttaminen on tärkeä elementti elinvoimaisen elokuvateollisuuden säilyttämisen kannalta, sillä sen myötä ulkomaalaisten elokuvantuotuottajien halukkuus työskennellä Skotlannissa lisääntyy. Ulkomaiset investoinnit voivat kuitenkin parhaimmillaan tarjota työtä myös skotlantilaiselle työvoimalle ja mahdollistaa paikallisten elokuvantekijöiden asettumisen Skotlantiin. Vaikka Skotlanti onkin maantieteellisesti kaukana Iso-Britannian päätösvallasta, sen henkeäsalpaavat maisemat ja moneen mukautuvat kaupunkiympäristöt ovat sen suurin valttikortti. Brexitin vaikutus kansainväliseen liikkuvuuteen ja rahoitusmahdollisuuksiin tullaan näkemään lähivuosina. Tutkimuksesta voidaan silti päätellä skotlantilaisen elokuvateollisuuden elävän kasvukautta. Keskeisinä rakennuspalikoina toimivat elokuva- ja tv-tuotannon kehittämiseen keskittyvän yksikön, sekä laaja-alaisen elokuvastudion perustaminen, joiden suurimpana mahdollistajana on toiminut julkisen sektorin rahoituksen lisääntyminen ja Creative Scotlandin yhteistyö paikallisten toimijoiden kanssa