2,661 research outputs found
Bayesian spline-based hidden Markov models with applications to actimetry data and sleep analysis
B-spline-based hidden Markov models employ B-splines to specify the emission distributions, offering a more flexible modeling approach to data than conventional parametric HMMs. We introduce a Bayesian framework for inference, enabling the simultaneous estimation of all unknown model parameters including the number of states. A parsimonious knot configuration of the B-splines is identified by the use of a trans-dimensional Markov chain sampling algorithm, while model selection regarding the number of states can be performed based on the marginal likelihood within a parallel sampling framework. Using extensive simulation studies, we demonstrate the superiority of our methodology over alternative approaches as well as its robustness and scalability. We illustrate the explorative use of our methods for data on activity in animals, that is whitetip-sharks. The flexibility of our Bayesian approach also facilitates the incorporation of more realistic assumptions and we demonstrate this by developing a novel hierarchical conditional HMM to analyse human activity for circadian and sleep modeling. Supplementary materials for this article are available online
Meta-learning algorithms and applications
Meta-learning in the broader context concerns how an agent learns about their own learning, allowing them to improve their learning process. Learning how to learn is not only beneficial for humans, but it has also shown vast benefits for improving how machines learn. In the context of machine learning, meta-learning enables models to improve their learning process by selecting suitable meta-parameters that influence the learning. For deep learning specifically, the meta-parameters typically describe details of the training of the model but can also include description of the model itself - the architecture. Meta-learning is usually done with specific goals in mind, for example trying to improve ability to generalize or learn new concepts from only a few examples.
Meta-learning can be powerful, but it comes with a key downside: it is often computationally costly. If the costs would be alleviated, meta-learning could be more accessible to developers of new artificial intelligence models, allowing them to achieve greater goals or save resources. As a result, one key focus of our research is on significantly improving the efficiency of meta-learning. We develop two approaches: EvoGrad and PASHA, both of which significantly improve meta-learning efficiency in two common scenarios. EvoGrad allows us to efficiently optimize the value of a large number of differentiable meta-parameters, while PASHA enables us to efficiently optimize any type of meta-parameters but fewer in number.
Meta-learning is a tool that can be applied to solve various problems. Most commonly it is applied for learning new concepts from only a small number of examples (few-shot learning), but other applications exist too. To showcase the practical impact that meta-learning can make in the context of neural networks, we use meta-learning as a novel solution for two selected problems: more accurate uncertainty quantification (calibration) and general-purpose few-shot learning. Both are practically important problems and using meta-learning approaches we can obtain better solutions than the ones obtained using existing approaches. Calibration is important for safety-critical applications of neural networks, while general-purpose few-shot learning tests model's ability to generalize few-shot learning abilities across diverse tasks such as recognition, segmentation and keypoint estimation.
More efficient algorithms as well as novel applications enable the field of meta-learning to make more significant impact on the broader area of deep learning and potentially solve problems that were too challenging before. Ultimately both of them allow us to better utilize the opportunities that artificial intelligence presents
Statistical analysis of grouped text documents
L'argomento di questa tesi sono i modelli statistici per l'analisi dei dati testuali, con particolare attenzione ai contesti in cui i campioni di testo sono raggruppati.
Quando si ha a che fare con dati testuali, il primo problema è quello di elaborarli, per renderli compatibili dal punto di vista computazionale e metodologico con i metodi matematici e statistici prodotti e continuamente sviluppati dalla comunità scientifica. Per questo motivo, la tesi passa in rassegna i metodi esistenti per la rappresentazione analitica e l'elaborazione di campioni di dati testuali, compresi i "Vector Space Models", le "rappresentazioni distribuite" di parole e documenti e i "contextualized embeddings". Questa rassegna comporta la standardizzazione di una notazione che, anche all'interno dello stesso approccio di rappresentazione, appare molto eterogenea in letteratura.
Vengono poi esplorati due domini di applicazione: i social media e il turismo culturale. Per quanto riguarda il primo, viene proposto uno studio sull'autodescrizione di gruppi diversi di individui sulla piattaforma StockTwits, dove i mercati finanziari sono gli argomenti dominanti. La metodologia proposta ha integrato diversi tipi di dati, sia testuali che variabili categoriche. Questo studio ha agevolato la comprensione sul modo in cui le persone si presentano online e ha trovato stutture di comportamento ricorrenti all'interno di gruppi di utenti.
Per quanto riguarda il turismo culturale, la tesi approfondisce uno studio condotto nell'ambito del progetto "Data Science for Brescia - Arts and Cultural Places", in cui è stato addestrato un modello linguistico per classificare le recensioni online scritte in italiano in quattro aree semantiche distinte relative alle attrazioni culturali della città di Brescia. Il modello proposto permette di identificare le attrazioni nei documenti di testo, anche quando non sono esplicitamente menzionate nei metadati del documento, aprendo così la possibilità di espandere il database relativo a queste attrazioni culturali con nuove fonti, come piattaforme di social media, forum e altri spazi online.
Infine, la tesi presenta uno studio metodologico che esamina la specificità di gruppo delle parole, analizzando diversi stimatori di specificità di gruppo proposti in letteratura. Lo studio ha preso in considerazione documenti testuali raggruppati con variabile di "outcome" e variabile di gruppo. Il suo contributo consiste nella proposta di modellare il corpus di documenti come una distribuzione multivariata, consentendo la simulazione di corpora di documenti di testo con caratteristiche predefinite. La simulazione ha fornito preziose indicazioni sulla relazione tra gruppi di documenti e parole. Inoltre, tutti i risultati possono essere liberamente esplorati attraverso un'applicazione web, i cui componenti sono altresì descritti in questo manoscritto.
In conclusione, questa tesi è stata concepita come una raccolta di studi, ognuno dei quali suggerisce percorsi di ricerca futuri per affrontare le sfide dell'analisi dei dati testuali raggruppati.The topic of this thesis is statistical models for the analysis of textual data, emphasizing contexts in which text samples are grouped.
When dealing with text data, the first issue is to process it, making it computationally and methodologically compatible with the existing mathematical and statistical methods produced and continually developed by the scientific community. Therefore, the thesis firstly reviews existing methods for analytically representing and processing textual datasets, including Vector Space Models, distributed representations of words and documents, and contextualized embeddings. It realizes this review by standardizing a notation that, even within the same representation approach, appears highly heterogeneous in the literature.
Then, two domains of application are explored: social media and cultural tourism. About the former, a study is proposed about self-presentation among diverse groups of individuals on the StockTwits platform, where finance and stock markets are the dominant topics. The methodology proposed integrated various types of data, including textual and categorical data. This study revealed insights into how people present themselves online and found recurring patterns within groups of users.
About the latter, the thesis delves into a study conducted as part of the "Data Science for Brescia - Arts and Cultural Places" Project, where a language model was trained to classify Italian-written online reviews into four distinct semantic areas related to cultural attractions in the Italian city of Brescia. The model proposed allows for the identification of attractions in text documents, even when not explicitly mentioned in document metadata, thus opening possibilities for expanding the database related to these cultural attractions with new sources, such as social media platforms, forums, and other online spaces.
Lastly, the thesis presents a methodological study examining the group-specificity of words, analyzing various group-specificity estimators proposed in the literature. The study considered grouped text documents with both outcome and group variables. Its contribution consists of the proposal of modeling the corpus of documents as a multivariate distribution, enabling the simulation of corpora of text documents with predefined characteristics. The simulation provided valuable insights into the relationship between groups of documents and words. Furthermore, all its results can be freely explored through a web application, whose components are also described in this manuscript.
In conclusion, this thesis has been conceived as a collection of papers. It aimed to contribute to the field with both applications and methodological proposals, and each study presented here suggests paths for future research to address the challenges in the analysis of grouped textual data
Essays on Corporate Disclosure of Value Creation
Information on a firm’s business model helps investors understand an entity’s resource requirements, priorities for action, and prospects (FASB, 2001, pp. 14-15; IASB, 2010, p. 12). Disclosures of strategy and business model (SBM) are therefore considered a central element of effective annual report commentary (Guillaume, 2018; IIRC, 2011). By applying natural language processing techniques, I explore what SBM disclosures look like when management are pressed to say something, analyse determinants of cross-sectional variation in SBM reporting properties, and assess whether and how managers respond to regulatory interventions seeking to promote SBM annual report commentary. This dissertation contains three main chapters. Chapter 2 presents a systematic review of the academic literature on non-financial reporting and the emerging literature on SBM reporting. Here, I also introduce my institutional setting. Chapter 3 and Chapter 4 form the empirical sections of this thesis. In Chapter 3, I construct the first large sample corpus of SBM annual report commentary and provide the first systematic analysis of the properties of such disclosures. My topic modelling analysis rejects the hypothesis that such disclosure is merely padding; instead finding themes align with popular strategy frameworks and management tailor the mix of SBM topics to reflect their unique approach to value creation. However, SBM commentary is less specific, less precise about time horizon (short- and long-term), and less balanced (more positive) in tone relative to general management commentary. My findings suggest symbolic compliance and legitimisation characterize the typical annual report discussion of SBM. Further analysis identifies proprietary cost considerations and obfuscation incentives as key determinants of symbolic reporting. In Chapter 4, I seek evidence on how managers respond to regulatory mandates by adapting the properties of disclosure and investigate whether the form of the mandate matters. Using a differences-in-differences research design, my results suggest a modest incremental response by treatment firms to the introduction of a comply or explain provision to provide disclosure on strategy and business model. In contrast, I find a substantial response to enacting the same requirements in law. My analysis provides clear and consistent evidence that treatment firms incrementally increase the volume of SBM disclosure, improve coverage across a broad range of topics as well as providing commentary with greater focus on the long term. My results point to substantial changes in SBM reporting properties following regulatory mandates, but the form of the mandate does matter. Overall, this dissertation contributes to the accounting literature by examining how firms discuss a central topic to economic decision making in annual reports and how firms respond to different forms of disclosure mandate. Furthermore, the results of my analysis are likely to be of value for regulators and policymakers currently reviewing or considering mandating disclosure requirements. By examining how companies adapt their reporting to different types of regulations, this study provides an empirical basis for recalibrating SBM disclosure mandates, thereby enhancing the information set of capital market participants and promoting stakeholder engagement in a landscape increasingly shaped by non-financial information
Clustering MIC data through Bayesian mixture models: an application to detect M. Tuberculosis resistance mutations
Antimicrobial resistance is becoming a major threat to public health
throughout the world. Researchers are attempting to contrast it by developing
both new antibiotics and patient-specific treatments. In the second case,
whole-genome sequencing has had a huge impact in two ways: first, it is
becoming cheaper and faster to perform whole-genome sequencing, and this makes
it competitive with respect to standard phenotypic tests; second, it is
possible to statistically associate the phenotypic patterns of resistance to
specific mutations in the genome. Therefore, it is now possible to develop
catalogues of genomic variants associated with resistance to specific
antibiotics, in order to improve prediction of resistance and suggest
treatments. It is essential to have robust methods for identifying mutations
associated to resistance and continuously updating the available catalogues.
This work proposes a general method to study minimal inhibitory concentration
(MIC) distributions and to identify clusters of strains showing different
levels of resistance to antimicrobials. Once the clusters are identified and
strains allocated to each of them, it is possible to perform regression method
to identify with high statistical power the mutations associated with
resistance. The method is applied to a new 96-well microtiter plate used for
testing M. Tuberculosis
2023-2024 Catalog
The 2023-2024 Governors State University Undergraduate and Graduate Catalog is a comprehensive listing of current information regarding:Degree RequirementsCourse OfferingsUndergraduate and Graduate Rules and Regulation
Qualitative analysis of online reviews of users of hospitality services
Савремено друштво се све више ослања на акумулирана мишљења којa могу да пронађу на интернету. Допринос корисника на технолошким платформама омогућава олакшану интеракцију између истомишљеника заједничких интересовања, и на тај начин се олакшава процес доношења одлука. У оквиру окваквог технолошког контекста, организације у услужном сектору попут туризма и гоститељства, морају да се суоче са изазовом управљања садржајима од стране корисника. Маркетиншки стручњаци су нашли начин да искористе овакве интеракције што истиче значај имплементације нових знања у организацијама које ће помоћи у прикупљању, анализирању, тумачењу и управљању онлајн друштвеним утицајима. Предмет истраживања докторске дисертације је квалитативна анализа онлајн рецензија корисника угоститељских услуга у Србији. У поређењу са нумеричким оценама корисника, текстуалне рецензије одражавају задовољство или незадовољство корисника, али на много детаљнији начин јер садрже више информација и на тај начин се стиче реаланији увид у стварна искуства корисника. Поред квалитативне обраде текста рецензија, идентификација врсте и значаја детерминанти задовољства и незадовољства у рецензијама корисника хотелских (у зависности од типа - градски, планински или бањски) и ресторанских услуга је један од главних задатака дисертације. За потребе истраживања прикупљене су рецензије хотела и ресторана у Србији. Коришћена је комбинација квалитативних и квантитативних метода у циљу доказивања постављених хипотеза. Од квалитативних анализа примењене су анализа фреквенције речи, анализа дужине рецензија, анализа сентимента, анализа читљивости и Латентна Дирихлеова Алокација (ЛДА). Од квантитативних метода коришћена је вишеструка регресија за утврђивање међусобних утицаја варијабли. Анализом фреквенције речи издвојене су речи које су се најчешће појављивале у рецензијама хотела и ресторана. Када су у питању хотели, у позитивним рецензијама су се појављивале речи које су се односиле на карактеристичне услуге које се пружају у одређеном типу хотела и садржале су више позитивних описних придева везаних за искуство конзумације. У негативним рецензијама хотела, без обзира на тип, чешће су се појављивали негативни описни придеви и речи које су указивале на материјалне (опипљиве) елементе хотелског производа. У позитивним рецензијама ресторана је такође присутно доста позитивних описних придева, а у негативним рецензијама је наглашен негативни аспект цене услуга у ресторану. Иако су рецензије негативне, у њима је присутно доста позитивних описних придева, што указује на то да је било аспеката услуге којима су били задовољни. Анализа дужине рецензија је показала да се у рецензијама, како хотела тако и ресторана, много више речи и реченица користи за описивање негативног искуства него позитивног. Анализа читљивости је спроведена с циљем утврђивања колико је просечно година формалног образовања неопходно за разумевање рецензија на прво читање. Резултати анализе су показали да вредности индекса читљивости варирају од веома ниског (рецензије које су разумљиве свима) до веома високог (изузетно тешке за разумевање). Просечна вредност индекса читљивости указује да читаоци морају бити завршне године средње школе за разумевање текста на прво читање. Анализом сентимента анализирана су осећања у рецензијама. Распон сентимента варира од екстремно негативних до екстремно позитивних осећања, али највећи број рецензија, како позитивних тако и негативних, садржао је неутрална и позитивна осећања. Анализирајући сентимент у рецензијама ресторана, добијени су слични резултати као и код рецензија хотела. Распон вредности сентимента варира од екстремно негативних до екстремно позитивних осећања, а са порастом оцене, расте и вредност сентимента. Овакви резултати могу указивати на то да, иако су били незадовољни, искуство корисника није праћено негативним осећањима, која су често заслужна за ширење негативних електронских препорука. Применом ЛДА издвојене су детерминанте задовољства и незадовољства услугама у хотелима (у зависности од типа хотела и категорије, као и од типа госта) и ресторанима. Полазећи од претпоставке да се детерминанте задовољства и незадовољства разликују у зависности од типа хотела, категорије и типа госта добијени су резултати који делимично потврђују ове претпоставке. Претпостављено је и да се различите детерминанте утичу на задовољство и незадовољство услугама у ресторанима, што је делимично потврђено. Применом вишеструке регресије тестирани су утицаји техничких карактеристика рецензија (поларитет, читљивост и дужина) на оцене и корисност рецензија. Добијени резултати су потврдили позитивни утицај сентимента и негативни утицај дужине рецензија на оцене корисника код хотелских рецензија, а у случају ресторана нису потврђени претпостављени утицаји. У случају утицаја техничких карактеристика рецензија хотела на корисност није утврђен значајан утицај, док је код рецензија ресторана пронађен позитиван утицај дужине и негативан утицај сентимента на корисност. Резултати добијени у овој дисертацији имају бројне теоријске и практичне импликације на угоститељску делатност. Будући да је задовољство корисника интегрални део угоститељске делатности, идентификоване детерминанте задовољства и незадовољства корисника могу угоститељима помоћи да унапреде своје пословање. На основу утврђеног утицаја техничких карактеристика рецензија на оцену и корисност, угоститељи могу да теже томе да побољшају перформансе рецензија које добијају од корисника, тако што ће, пружањем услуге врхунског квалитета, смањити негативне и дуге рецензије.Savremeno društvo se sve više oslanja na akumulirana mišljenja koja mogu da pronađu na internetu. Doprinos korisnika na tehnološkim platformama omogućava olakšanu interakciju između istomišljenika zajedničkih interesovanja, i na taj način se olakšava proces donošenja odluka. U okviru okvakvog tehnološkog konteksta, organizacije u uslužnom sektoru poput turizma i gostiteljstva, moraju da se suoče sa izazovom upravljanja sadržajima od strane korisnika. Marketinški stručnjaci su našli način da iskoriste ovakve interakcije što ističe značaj implementacije novih znanja u organizacijama koje će pomoći u prikupljanju, analiziranju, tumačenju i upravljanju onlajn društvenim uticajima. Predmet istraživanja doktorske disertacije je kvalitativna analiza onlajn recenzija korisnika ugostiteljskih usluga u Srbiji. U poređenju sa numeričkim ocenama korisnika, tekstualne recenzije odražavaju zadovoljstvo ili nezadovoljstvo korisnika, ali na mnogo detaljniji način jer sadrže više informacija i na taj način se stiče realaniji uvid u stvarna iskustva korisnika. Pored kvalitativne obrade teksta recenzija, identifikacija vrste i značaja determinanti zadovoljstva i nezadovoljstva u recenzijama korisnika hotelskih (u zavisnosti od tipa - gradski, planinski ili banjski) i restoranskih usluga je jedan od glavnih zadataka disertacije. Za potrebe istraživanja prikupljene su recenzije hotela i restorana u Srbiji. Korišćena je kombinacija kvalitativnih i kvantitativnih metoda u cilju dokazivanja postavljenih hipoteza. Od kvalitativnih analiza primenjene su analiza frekvencije reči, analiza dužine recenzija, analiza sentimenta, analiza čitljivosti i Latentna Dirihleova Alokacija (LDA). Od kvantitativnih metoda korišćena je višestruka regresija za utvrđivanje međusobnih uticaja varijabli. Analizom frekvencije reči izdvojene su reči koje su se najčešće pojavljivale u recenzijama hotela i restorana. Kada su u pitanju hoteli, u pozitivnim recenzijama su se pojavljivale reči koje su se odnosile na karakteristične usluge koje se pružaju u određenom tipu hotela i sadržale su više pozitivnih opisnih prideva vezanih za iskustvo konzumacije. U negativnim recenzijama hotela, bez obzira na tip, češće su se pojavljivali negativni opisni pridevi i reči koje su ukazivale na materijalne (opipljive) elemente hotelskog proizvoda. U pozitivnim recenzijama restorana je takođe prisutno dosta pozitivnih opisnih prideva, a u negativnim recenzijama je naglašen negativni aspekt cene usluga u restoranu. Iako su recenzije negativne, u njima je prisutno dosta pozitivnih opisnih prideva, što ukazuje na to da je bilo aspekata usluge kojima su bili zadovoljni. Analiza dužine recenzija je pokazala da se u recenzijama, kako hotela tako i restorana, mnogo više reči i rečenica koristi za opisivanje negativnog iskustva nego pozitivnog. Analiza čitljivosti je sprovedena s ciljem utvrđivanja koliko je prosečno godina formalnog obrazovanja neophodno za razumevanje recenzija na prvo čitanje. Rezultati analize su pokazali da vrednosti indeksa čitljivosti variraju od veoma niskog (recenzije koje su razumljive svima) do veoma visokog (izuzetno teške za razumevanje). Prosečna vrednost indeksa čitljivosti ukazuje da čitaoci moraju biti završne godine srednje škole za razumevanje teksta na prvo čitanje. Analizom sentimenta analizirana su osećanja u recenzijama. Raspon sentimenta varira od ekstremno negativnih do ekstremno pozitivnih osećanja, ali najveći broj recenzija, kako pozitivnih tako i negativnih, sadržao je neutralna i pozitivna osećanja. Analizirajući sentiment u recenzijama restorana, dobijeni su slični rezultati kao i kod recenzija hotela. Raspon vrednosti sentimenta varira od ekstremno negativnih do ekstremno pozitivnih osećanja, a sa porastom ocene, raste i vrednost sentimenta. Ovakvi rezultati mogu ukazivati na to da, iako su bili nezadovoljni, iskustvo korisnika nije praćeno negativnim osećanjima, koja su često zaslužna za širenje negativnih elektronskih preporuka. Primenom LDA izdvojene su determinante zadovoljstva i nezadovoljstva uslugama u hotelima (u zavisnosti od tipa hotela i kategorije, kao i od tipa gosta) i restoranima. Polazeći od pretpostavke da se determinante zadovoljstva i nezadovoljstva razlikuju u zavisnosti od tipa hotela, kategorije i tipa gosta dobijeni su rezultati koji delimično potvrđuju ove pretpostavke. Pretpostavljeno je i da se različite determinante utiču na zadovoljstvo i nezadovoljstvo uslugama u restoranima, što je delimično potvrđeno. Primenom višestruke regresije testirani su uticaji tehničkih karakteristika recenzija (polaritet, čitljivost i dužina) na ocene i korisnost recenzija. Dobijeni rezultati su potvrdili pozitivni uticaj sentimenta i negativni uticaj dužine recenzija na ocene korisnika kod hotelskih recenzija, a u slučaju restorana nisu potvrđeni pretpostavljeni uticaji. U slučaju uticaja tehničkih karakteristika recenzija hotela na korisnost nije utvrđen značajan uticaj, dok je kod recenzija restorana pronađen pozitivan uticaj dužine i negativan uticaj sentimenta na korisnost. Rezultati dobijeni u ovoj disertaciji imaju brojne teorijske i praktične implikacije na ugostiteljsku delatnost. Budući da je zadovoljstvo korisnika integralni deo ugostiteljske delatnosti, identifikovane determinante zadovoljstva i nezadovoljstva korisnika mogu ugostiteljima pomoći da unaprede svoje poslovanje. Na osnovu utvrđenog uticaja tehničkih karakteristika recenzija na ocenu i korisnost, ugostitelji mogu da teže tome da poboljšaju performanse recenzija koje dobijaju od korisnika, tako što će, pružanjem usluge vrhunskog kvaliteta, smanjiti negativne i duge recenzije.Modern society is increasingly relying on the accumulated opinions of its peers that they can find on the Internet. The contribution of consumers on technology platforms enables easier interaction between like-minded people with common interests, and thus facilitates the decision-making process. Within this technological context, service sector organizations such as tourism and hospitality have to face the challenge of consumer-driven content management. Marketing experts have found a way to take advantage of such interactions, which emphasizes the importance of implementing new knowledge in organizations that will help collect, analyze, interpret and manage online social influences. The subject of the doctoral dissertation research is the qualitative analysis of online reviews of consumers of catering services in Serbia. Compared to numerical ratings of users, text reviews reflect customer satisfaction or dissatisfaction but in a much more detailed way because they contatin more information, and thus gain a realistic insight into real consumer experiences. Identifying the type and importance of determinants of satisfaction and dissatisfaction in consumer reviews according to hotel type (city, mountain or spa hotel) is one of the main tasks of the dissertation. For the puroposes of the research, reviews of hotels and restaurants in Serbia were collected. A combination of qualitative and quantitative methods was used in order to prove the set hypotheses. Qualitative analyzes that were applied are word frequency analysis, review length analysis, sentiment analysis, readability analysis and Latent Dirichlet Allocation (LDA). Among the quantitative methods, multiple regression was used to determine the mutual influence of variables. By analyzing the frequency of words, the words that appeared most often in reviews of hotels and restaurants were singled out. When it comes to hotels, positive reviews featured words that referred to the characteristics services provided in a certain type of hotel and contained more positive descriptive adjectives related to the experience of consumption. In negative hotel reviews, regardless of the hotel type, negative descriptive adjectives and words that indicated the material (tangible) elements of the hotel products appeared more often. In the positive reviews of restaurants, there are also a lot of positive descriptive adjectives, and in negative reviews, the negative aspect of the price of restaurant’s services is emphasized. Although the reviews are negative, there are a lot of positive descriptive adjectives in them, indicating that there were aspects of the services that they were satisfied with. The analysis of the length of reviews showed that in the reviews of both hotels and restaurants, many more words and sentences are used to describe a negative expericence than a positive one. A readability analysis was conducted to determine the average number of years of formal education necessary to understand reviews on first reading. The results of analysis showed that the values of the readability index vary form very low (reviews that are understandable to everyone) to very high (extremly difficult to understand). The average value of the readability index indicates that readers must be in their senior years of high school to understand the text on the first reading. Sentiment analysis analyzed the feelings in the reviews. The range of sentiment values varies from extremely negative to extremly positive sentiments, but the largest number of reviews, both positive and negative, contained neutral and positive sentiments. By analyzing sentiment in restaurant reviews, similar resutls were obtained as in hotel reviews. The range of sentiment values vaires from extremely negative to extremely positive sentiments, and as the rating increases, so does the value of the sentiment. Such results may indicate that, although they were dissatisfied, the user experience was not accompanied by negative feeling, which are often responsible for the spread of negative electronic recommendation. Using LDA, the determinants of satisfaction and dissatisfaction with services in hotels (depending on the type of hotel and category, as well as the type of traveler) and restaurants were isolated. Based on the assumption that the determinants of satisfaction and dissatisfaction differ depending on the type of hotel, category and type of travelers, obtained results partially confirm these assumptions. It was assumed that different determinants influence satisfaction and dissatisfaction with restaurant services, which was partially confirmed. By using multiple regression, the effects of the technical characteristics of reviews (polarity, readability and length) on the ratings and helpfulness of the reviews were tested. The obtained results confirmed the positive impact of sentiment and the negative impact of the length of reviews on user rating of hotel reviews. In the case of restaurants, the assumed impacts were not confirmed. In the case of the influence of tecnical characteristics of hotel reviews on reviews helpfulness, no significant influence was found, while in the case of restaurant reviews, a positive influence of length and a negative influence of sentiment on review helpfulness were found. The results obtained in this dissertation have numerous theoretical and practical implications for the hospitality industry. Since customer satisfaction is an integral part of the hospitality business, the identified determinants of customer satisfaction and dissatisfaction can help hoteliers and restauraters improve their business. Based on the established impact of technical characteristics of review on rating and helpfulness, hoteliers and restauraters can strive to improve the performance of reviews they receive from customers by reducing negative and long reviews by providing superior service
Searching for Themes in a Chamber full of Noise? How Language Affects United Nations’ Actions and Decisions
Against a scholarly mountain of literature on the United Nations, it is astounding how profoundly little we know about the decision-making processes of its most powerful and secretive body, the UN Security Council. In particular, no study has systematically investigated the rhetoric in the Council and assessed its impact on actions and decisions in authorized resolutions. Since diplomats, lawyers, and policymakers held almost 80,000 speeches in public debates between 1995 and 2018 alone, one has to wonder, do these speeches matter? Do they affect intergovernmental decision-making procedures? Do they amount to anything in world politics? And if so, what is their effect? The lack of answers to these questions shows the need for a theory-driven systematic, and rigorous empirical investigation of Council rhetoric
- …