O fenômeno da ambiguidade lexical foi o tópico central desta pesquisa, especialmente no que diz respeito às relações entre acepções de formas gráficas ambíguas e aos padrões de distribuição de acepções de palavras polissêmicas na língua, isto é, de palavras cujas acepções são semanticamente relacionadas. Este trabalho situa-se como uma proposta de interface entre explorações computacionais da ambiguidade lexical, especificamente de processamento de linguagem natural, e investigações de cunho teórico sobre o fenômeno do significado lexical. Partimos das noções de polissemia e de homonímia como correspondentes, respectivamente, ao caso de uma palavra com múltiplas acepções relacionadas e ao de duas (ou mais) palavras cujas formas gráficas coincidem, mas que apresentam acepções não relacionadas sincronicamente. Como objetivo último deste estudo, pretendia-se confirmar se as palavras mais polissêmicas teriam acepções menos uniformemente distribuídas no corpus, apresentando acepções predominantes, que ocorreriam com maior frequência. Para analisar esses aspectos, implementamos um algoritmo de desambiguação lexical, uma versão adaptada do algoritmo de Lesk (Lesk, 1986; Jurafsky & Martin, 2000), escolhido com base nos recursos linguísticos disponíveis para o português. Tendo como hipótese a noção de que palavras mais frequentes na língua tenderiam a ser mais polissêmicas, selecionamos do corpus (Mac-Morpho) aquelas com maiores ocorrências. Considerando-se o interesse em palavras de conteúdo e em casos de ambiguidade mais estritamente em nível semântico, optamos por realizar os testes apresentados neste trabalho apenas para substantivos. Os resultados obtidos com o algoritmo de desambiguação que implementamos superaram o método baseline baseado na heurística da acepção mais frequente: obtivemos 63% de acertos contra 50% do baseline para o total dos dados desambiguados. Esses resultados foram obtidos através do procedimento de desambiguação de pseudo-palavras (formadas ao acaso), utilizado em casos em que não se tem à disposição corpora semanticamente anotados. No entanto, em razão da dependência de inventários fixos de acepções oriundos de dicionários, pesquisamos maneiras alternativas de categorizar as acepções de uma palavra. Tomando como base o trabalho de Sproat & VanSanten (2001), implementamos um método que permite atribuir valores numéricos que atestam o quanto uma palavra se afastou da monossemia dentro de um determinado corpus. Essa medida, cunhada pelos autores do trabalho original como índice de polissemia, baseia-se no agrupamento de palavras co-ocorrentes à palavra-alvo da desambiguação de acordo com suas similaridades contextuais. Propusemos, neste trabalho, o uso de uma segunda medida, mencionada pelos autores apenas como um exemplo das aplicações potenciais do método a serem exploradas: a clusterização de co-ocorrentes com base em similaridades de contextos de uso. Essa segunda medida é obtida de forma que se possa verificar a proximidade entre acepções e a quantidade de acepções que uma palavra exibe no corpus. Alguns aspectos apontados nos resultados indicam o potencial do método de clusterização: os agrupamentos de co-ocorrentes obtidos são ponderados, ressaltando os grupos mais proeminentes de vizinhos da palavra-alvo; o fato de que os agrupamentos aproximam-se uns dos outros por medidas de similaridade contextual, o que pode servir para distinguir tendências homonímicas ou polissêmicas. Como exemplo, temos os clusters obtidos para a palavra produção: um relativo à ideia de produção literária e outro relativo à de produção agrícola. Esses dois clusters apresentaram distanciamento considerável, situando-se na faixa do que seria considerado um caso de polissemia, e apresentaram ambos pesos significativos, isto é, foram compostos por palavras mais relevantes. Identificamos três fatores principais que limitaram as análises a partir dos dados obtidos: o viés político-jornalístico do corpus que utilizamos (Mac-Morpho) e a necessidade de serem feitos mais testes variando os parâmetros de seleção de coocorrentes, uma vez que os parâmetros que utilizamos devem variar para outros corpora e, especialmente, pelo fato de termos realizados poucos testes para definir quais valores utilizaríamos para esses parâmetro, que são decisivos para a quantidade de palavras co-ocorrentes relevantes para os contextos de uso da palavra-alvo. Considerando-se tanto as vantagens quanto as limitações que observamos a partir dos resultados da clusterização, planejamos delinear um método sincrônico (que prescinde da documentação histórica das palavras) e computacional que permita distinguir casos de polissemia e de homonímia de forma mais sistemática e abrangendo uma maior quantidade de dados. Entendemos que um método dessa natureza pode ser de grade valia para os estudos do significado no nível lexical, permitindo o estabelecimento de um método objetivo e baseado em dados de uso da língua que vão além de exemplos pontuais. / The phenomenon of lexical ambiguity was the central topic of this research, especially with regard to relations between meanings of ambiguous graphic forms, and to patterns of distribution of the meanings of polysemous words in the language, that is, of words whose meanings are semantically related. This work is set on the interface between computational explorations of lexical ambiguity, specifically natural language processing, and theoretical investigations on the nature of research on the lexical meaning phenomenon. We assume the notions of polysemy and homonymy as corresponding, respectively, to the case of a word with multiple related meanings, and two (or more) words whose graphic forms coincide, but have unrelated meanings. The ultimate goal of this study was to confirm that the most polysemous words have meanings less evenly distributed in the corpus, with predominant meanings which occur more frequently. To examine these aspects, we implemented a word sense disambiguation algorithm, an adapted version of Lesk algorithm (Lesk, 1986; Jurafsky & Martin, 2000), chosen on the basis of the availability of language resources in Portuguese. From the hypothesis that the most frequent words in the language tend to be more polysemic, we selected from the corpus (Mac-Morpho) those words with the highest number occurrences. Considering our interest in content words and in cases of ambiguity more strictly to the semantic level, we decided to conduct the tests presented in this research only for nouns. The results obtained with the disambiguation algorithm implemented surpassed those of the baseline method based on the heuristics of the most frequent sense: we obtained 63% accuracy against 50% of baseline for all the disambiguated data. These results were obtained with the disambiguation procedure of pseudowords (formed at random), which used in cases where semantically annotated corpora are not available. However, due to the dependence of this disambiguation method on fixed inventories of meanings from dictionaries, we searched for alternative ways of categorizing the meanings of a word. Based on the work of Sproat & VanSanten (2001), we implemented a method for assigning numerical values that indicate how much one word is away from monosemy within a certain corpus. This measure, named by the authors of the original work as polysemy index, groups co-occurring words of the target noun according to their contextual similarities. We proposed in this paper the use of a second measure, mentioned by the authors as an example of the potential applications of the method to be explored: the clustering of the co-occurrent words based on their similarities of contexts of use. This second measurement is obtained so as to show the closeness of meanings and the amount of meanings that a word displays in the corpus. Some aspects pointed out in the results indicate the potential of the clustering method: the obtained co-occurring clusters are weighted, highlighting the most prominent groups of neighbors of the target word; the fact that the clusters aproximate from each other to each other on the basis of contextual similarity measures, which can be used to distinguish homonymic from polysemic trends. As an example, we have the clusters obtained for the word production, one referring to the idea of literary production, and the other referring to the notion of agricultural production. These two clusters exhibited considerable distance, standing in the range of what would be considered a case of polysemy, and both showed significant weights, that is, were composed of significant and distintictive words. We identified three main factors that have limited the analysis of the data: the political-journalistic bias of the corpus we use (Mac-Morpho) and the need for further testing by varying the selection parameters of relevant cooccurent words, since the parameters used shall vary for other corpora, and especially because of the fact that we conducted only a few tests to determine the values for these parameters, which are decisive for the amount of relevant co-occurring words for the target word. Considering both the advantages and the limitations we observe from the results of the clusterization method, we plan to design a synchronous (which dispenses with the historical documentation of the words) and, computational method to distinguish cases of polysemy and homonymy more systematically and covering a larger amount of data. We understand that a method of this nature can be invaluable for studies of the meaning on the lexical level, allowing the establishment of an objective method based on language usage data and, that goes beyond specific examples.

This study’s purpose was to provide a deeper understanding regarding how millennials’ attitudes towards brands are influenced by online communication. With the aim of fulfilling the purpose of the study, two research questions of descriptive and explorative kind were stated; “How can the factors that influence millennials’ use of electronic word-of-mouth be described?” as well as “How does electronic word-of-mouth influence millennials’ brand attitude?”. In order to generate potential answers to the stated research questions, a conceptual framework was conducted by reviewing scholarly literature. The conceptual framework then provided the study with a theoretical foundation of which was utilized during both the data collection and the data analysis. Methodologically, this was a case study analyzing qualitative data that was collected through eleven semi-structured and in-depth interviews with both male and female millennials. The findings and conclusions of this study implied that electronic word-of-mouth has a meaningful impact on both the formation of and influence on attitudes towards brands amongst the millennials. Moreover, this was heavily dependent on the one disseminated it. However, with regard to the ever-evolving area of social network sites, other noteworthy factors such as millennials’ need for affiliation, aesthetically appealing firm-generated content and intense exposure to digital advertising were emphasized as components of which too formed their attitudes towards brands. Furthermore, the results suggested that adopting personalization- and social interaction strategies will encourage the spreading of positive electronic word-of-mouth. Lastly, positive electronic word-of-mouth was then for its part related to brand loyalty, which was reckoned to promote the persistency of positive brand attitudes.

Mo, Deyuan. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 153-167). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese; appendixes includes Chinese.

Representation of sentences that captures semantics is an essential part of natural language processing systems, such as information retrieval or machine translation. The representation of a sentence is commonly built by combining the representations of the words that the sentence consists of. Similarity between words is widely used as a proxy to evaluate semantic representations. Word similarity models are well-studied and are shown to positively correlate with human similarity judgements. Current evaluation of models of sentential similarity builds on the results obtained in lexical experiments. The main focus is how the lexical representations are used, rather than what they should be. It is often assumed that the optimal representations for word similarity are also optimal for sentence similarity. This work discards this assumption and systematically looks for lexical representations that are optimal for similarity measurement between sentences. We find that the best representation for word similarity is not always the best for sentence similarity and vice versa. The best models in word similarity tasks perform best with additive composition. However, the best result on compositional tasks is achieved with Kroneckerbased composition. There are representations that are equally good in both tasks when used with multiplicative composition. The systematic study of the parameters of similarity models reveals that the more information lexical representations contain, the more attention should be paid to noise. In particular, the word vectors in models with the feature size at the magnitude of the vocabulary size should be sparse, but if a small number of context features is used then the vectors should be dense. Given the right lexical representations, compositional operators achieve state-of-the-art performance, improving over models that use neural-word embeddings. To avoid overfitting, either several test datasets should be used or parameter selection should be based on parameters' average behaviours.

Fenomenet “influencer” har den senaste tiden på grund av den stora spridningen av sociala mediervärlden över blivit ett allt mer vardaglig uttryck inom marknadsföring. Namnet influencer kommer från engelskans influence. Vidare betyder det att man influerar någon, då bland annat till olika köp och livsstilsbeslut. Vilket har gjort influencers till en potentiell reklampelare. Detta då influencerns följare vill leva som influencer och därför vill köpa det den köper. Syftet med vår studie är att studera hur företag genom användning av influencers kan stärka sinavarumärken. Vidare studerar vi hur man som företag utför processen att välja en influencer med mål om att skapa störst möjlighet till stärkandet av varumärket. För att besvara frågeställningen valde vi att göra en kvalitativ studie med fem företag; Abacus Sportswear, Style by Mouche, Plodder PR och kommunikation, en PR och kommunikationsbyrå med fokus på mode/lifestyle och en PR och kommunikationsbyrå med fokus på skönhet. Vi valde att utföra semistrukturerade intervjuer medföretagen för att skapa en intervju med utrymme för följdfrågor och diskussion. Studien har visat att företag framförallt marknadsför sig genom influencers för att sprida varumärkeskännedom och på så vis även stärka sitt varumärke. Det är viktigt för företagen att influencern står för liknande värderingar, kan förmedla ett trovärdigt budskap och att de kan starta en spridning av word of mouth i en positiv riktning. Dock visar vår studie att dagens processer för att välja influencers till varumärken inte fokuserar tillräckligt på varumärkesstärkande utan främst på statistik. Vi har genom att koppla ihop teori och empiri kommit fram till att för att ett samarbete med influencers ska ha goda förutsättningar till att kunna stärka varumärket behöver företag förutom att studera statistik även studera influencerns förtroende, personlig intimitet och ifall influencern går i linje med varumärket. Detta beskrivs i form av en modell på sju steg. / The phenomenon of "influencer" has recently become an increasingly used expression in marketing because of the wide spread of social media across the globe. The name influencer comes from English influence. Furthermore, it means that you influence someone, for example, for different purchases and lifestyle decisions. Which has made influencers a potential advertisers. This is when the influencer's followers want to live as influences and therefore want to buy what they buy. The purpose of our study is to study how companies through the use of influencers can strengthen their brands. Furthermore, we study how, as a company, they perform the process of selecting an influencer with the goal of creating the greatest opportunity for strengthening the brand. In order to answer the question, we chose to do a qualitative study with five companies; Abacus Sportswear, Style by Mouche, Plodder PR and Communication, one PR and communications firm that specializes in clothing and finally a PR and communications firm that specializes in beauty. We chose to conduct semi-structured interviews with companies to create an interview with space for follow-up questions and discussion. The study has shown that companies primarily market through influencers to spread brand awareness and to strengthen their brand. It is important for companies that influencers accounts for similar values, so that they can convey a credible message and that they can start spreading word of mouth in a positive direction. However, our study shows that today's processes for choosing influencers for brands do not focus enough on brand strengths, but primarily on statistics. By linking theory and empirical evidence, we have found that, in order for cooperation with influencers to have good conditions for strengthening the brand, companies need to study the confidence of the influences, personal intimacy and the influencer goes in line with the brand, in addition to studying statistics. This is described in the form of a seven-step model. Our study will be written in Swedish.

Thesis. 1979. Ph.D.--Massachusetts Institute of Technology. Dept. of Linguistics and Philosophy. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND HUMANITIES. / Bibliography: leaves 382-385. / Ph.D.

O fenômeno da ambiguidade lexical foi o tópico central desta pesquisa, especialmente no que diz respeito às relações entre acepções de formas gráficas ambíguas e aos padrões de distribuição de acepções de palavras polissêmicas na língua, isto é, de palavras cujas acepções são semanticamente relacionadas. Este trabalho situa-se como uma proposta de interface entre explorações computacionais da ambiguidade lexical, especificamente de processamento de linguagem natural, e investigações de cunho teórico sobre o fenômeno do significado lexical. Partimos das noções de polissemia e de homonímia como correspondentes, respectivamente, ao caso de uma palavra com múltiplas acepções relacionadas e ao de duas (ou mais) palavras cujas formas gráficas coincidem, mas que apresentam acepções não relacionadas sincronicamente. Como objetivo último deste estudo, pretendia-se confirmar se as palavras mais polissêmicas teriam acepções menos uniformemente distribuídas no corpus, apresentando acepções predominantes, que ocorreriam com maior frequência. Para analisar esses aspectos, implementamos um algoritmo de desambiguação lexical, uma versão adaptada do algoritmo de Lesk (Lesk, 1986; Jurafsky & Martin, 2000), escolhido com base nos recursos linguísticos disponíveis para o português. Tendo como hipótese a noção de que palavras mais frequentes na língua tenderiam a ser mais polissêmicas, selecionamos do corpus (Mac-Morpho) aquelas com maiores ocorrências. Considerando-se o interesse em palavras de conteúdo e em casos de ambiguidade mais estritamente em nível semântico, optamos por realizar os testes apresentados neste trabalho apenas para substantivos. Os resultados obtidos com o algoritmo de desambiguação que implementamos superaram o método baseline baseado na heurística da acepção mais frequente: obtivemos 63% de acertos contra 50% do baseline para o total dos dados desambiguados. Esses resultados foram obtidos através do procedimento de desambiguação de pseudo-palavras (formadas ao acaso), utilizado em casos em que não se tem à disposição corpora semanticamente anotados. No entanto, em razão da dependência de inventários fixos de acepções oriundos de dicionários, pesquisamos maneiras alternativas de categorizar as acepções de uma palavra. Tomando como base o trabalho de Sproat & VanSanten (2001), implementamos um método que permite atribuir valores numéricos que atestam o quanto uma palavra se afastou da monossemia dentro de um determinado corpus. Essa medida, cunhada pelos autores do trabalho original como índice de polissemia, baseia-se no agrupamento de palavras co-ocorrentes à palavra-alvo da desambiguação de acordo com suas similaridades contextuais. Propusemos, neste trabalho, o uso de uma segunda medida, mencionada pelos autores apenas como um exemplo das aplicações potenciais do método a serem exploradas: a clusterização de co-ocorrentes com base em similaridades de contextos de uso. Essa segunda medida é obtida de forma que se possa verificar a proximidade entre acepções e a quantidade de acepções que uma palavra exibe no corpus. Alguns aspectos apontados nos resultados indicam o potencial do método de clusterização: os agrupamentos de co-ocorrentes obtidos são ponderados, ressaltando os grupos mais proeminentes de vizinhos da palavra-alvo; o fato de que os agrupamentos aproximam-se uns dos outros por medidas de similaridade contextual, o que pode servir para distinguir tendências homonímicas ou polissêmicas. Como exemplo, temos os clusters obtidos para a palavra produção: um relativo à ideia de produção literária e outro relativo à de produção agrícola. Esses dois clusters apresentaram distanciamento considerável, situando-se na faixa do que seria considerado um caso de polissemia, e apresentaram ambos pesos significativos, isto é, foram compostos por palavras mais relevantes. Identificamos três fatores principais que limitaram as análises a partir dos dados obtidos: o viés político-jornalístico do corpus que utilizamos (Mac-Morpho) e a necessidade de serem feitos mais testes variando os parâmetros de seleção de coocorrentes, uma vez que os parâmetros que utilizamos devem variar para outros corpora e, especialmente, pelo fato de termos realizados poucos testes para definir quais valores utilizaríamos para esses parâmetro, que são decisivos para a quantidade de palavras co-ocorrentes relevantes para os contextos de uso da palavra-alvo. Considerando-se tanto as vantagens quanto as limitações que observamos a partir dos resultados da clusterização, planejamos delinear um método sincrônico (que prescinde da documentação histórica das palavras) e computacional que permita distinguir casos de polissemia e de homonímia de forma mais sistemática e abrangendo uma maior quantidade de dados. Entendemos que um método dessa natureza pode ser de grade valia para os estudos do significado no nível lexical, permitindo o estabelecimento de um método objetivo e baseado em dados de uso da língua que vão além de exemplos pontuais. / The phenomenon of lexical ambiguity was the central topic of this research, especially with regard to relations between meanings of ambiguous graphic forms, and to patterns of distribution of the meanings of polysemous words in the language, that is, of words whose meanings are semantically related. This work is set on the interface between computational explorations of lexical ambiguity, specifically natural language processing, and theoretical investigations on the nature of research on the lexical meaning phenomenon. We assume the notions of polysemy and homonymy as corresponding, respectively, to the case of a word with multiple related meanings, and two (or more) words whose graphic forms coincide, but have unrelated meanings. The ultimate goal of this study was to confirm that the most polysemous words have meanings less evenly distributed in the corpus, with predominant meanings which occur more frequently. To examine these aspects, we implemented a word sense disambiguation algorithm, an adapted version of Lesk algorithm (Lesk, 1986; Jurafsky & Martin, 2000), chosen on the basis of the availability of language resources in Portuguese. From the hypothesis that the most frequent words in the language tend to be more polysemic, we selected from the corpus (Mac-Morpho) those words with the highest number occurrences. Considering our interest in content words and in cases of ambiguity more strictly to the semantic level, we decided to conduct the tests presented in this research only for nouns. The results obtained with the disambiguation algorithm implemented surpassed those of the baseline method based on the heuristics of the most frequent sense: we obtained 63% accuracy against 50% of baseline for all the disambiguated data. These results were obtained with the disambiguation procedure of pseudowords (formed at random), which used in cases where semantically annotated corpora are not available. However, due to the dependence of this disambiguation method on fixed inventories of meanings from dictionaries, we searched for alternative ways of categorizing the meanings of a word. Based on the work of Sproat & VanSanten (2001), we implemented a method for assigning numerical values that indicate how much one word is away from monosemy within a certain corpus. This measure, named by the authors of the original work as polysemy index, groups co-occurring words of the target noun according to their contextual similarities. We proposed in this paper the use of a second measure, mentioned by the authors as an example of the potential applications of the method to be explored: the clustering of the co-occurrent words based on their similarities of contexts of use. This second measurement is obtained so as to show the closeness of meanings and the amount of meanings that a word displays in the corpus. Some aspects pointed out in the results indicate the potential of the clustering method: the obtained co-occurring clusters are weighted, highlighting the most prominent groups of neighbors of the target word; the fact that the clusters aproximate from each other to each other on the basis of contextual similarity measures, which can be used to distinguish homonymic from polysemic trends. As an example, we have the clusters obtained for the word production, one referring to the idea of literary production, and the other referring to the notion of agricultural production. These two clusters exhibited considerable distance, standing in the range of what would be considered a case of polysemy, and both showed significant weights, that is, were composed of significant and distintictive words. We identified three main factors that have limited the analysis of the data: the political-journalistic bias of the corpus we use (Mac-Morpho) and the need for further testing by varying the selection parameters of relevant cooccurent words, since the parameters used shall vary for other corpora, and especially because of the fact that we conducted only a few tests to determine the values for these parameters, which are decisive for the amount of relevant co-occurring words for the target word. Considering both the advantages and the limitations we observe from the results of the clusterization method, we plan to design a synchronous (which dispenses with the historical documentation of the words) and, computational method to distinguish cases of polysemy and homonymy more systematically and covering a larger amount of data. We understand that a method of this nature can be invaluable for studies of the meaning on the lexical level, allowing the establishment of an objective method based on language usage data and, that goes beyond specific examples.

Advances in digital technology have recently allowed for richer text annotation in combination with authentic second language video media. As a result, many educational researchers are focusing increased attention on the effect this application of technology can have on second language acquisition. This study examines the comparative effectiveness of target vocabulary treatments with either native language (L1) definitions or target language (L2) definitions when target vocabulary is presented in either kana or kanji as a part of the subtitles of an L2 film based on participant performance on vocabulary assessments. This study also examines the participants' perceived levels of helpfulness of the varying word treatments. The results of the study suggest that providing annotations for target words in the L2 increases learning of that word more than L1 annotations for intermediate learners of Japanese. On the other hand, learners rated access to definitions in L1 as more helpful than L2 definitions, and they expressed their preference for understanding the story more than learning the target vocabulary.

<p>Vi vill reda ut vilka olika faktorer som kan ha betydelse för bloggar som trovärdig marknadsföringskanal.</p><p>Vi har använt oss av en kvalitativ ansats för att få en djupare förståelse för bloggar som ett marknadsföringsverktyg. Genom en deduktiv metod har vår teoretiska referensram utgjort utgångspunkten för vår empiriska data.  Vårt empiriska material har vi samlat in genom sex genomförda personliga intervjuer med bloggrelaterade personer. Därefter har vi ställt vårt resultat i relation till vår teori och utifrån vår frågeställning fört en diskussion.<strong></strong></p><p>Företag kan inte styra vad bloggaren skriver och det är viktigt att bloggen får behålla sin personliga karaktär, då det styrker trovärdigheten för denne som marknadsföringskanal. Bloggen ska inte verka i säljande syfte, utan mer som rekommendationer till läsarna. Bloggare kan i vissa sammanhang agera som opinionsledare och besitter förmågan att påverka en stor grupp av människor. MeWe-generationen är en viktig målgrupp för företag, eftersom de frekvent influeras av modebloggar. Våra slutsatser visar även att öppenhet och relationer är viktiga begrepp vad gäller marknadsföring via bloggar.</p> / <p>We want to examine what different elements that can be of importance to blogs as a trustworthy marketing channel.</p><p>We have used a qualitative approach to be able to get deeper understanding of blogs as a marketing tool. Through a deductive method our theoretical frame of reference has made the base for our empirical data. Our empirical material we have collected by executing six personal interviews with blog related people. We have then come to our conclusions by analysing our theoretical and empirical material in relation to each other.<strong></strong></p><p>Companies cannot control what the blogger is writing and it is important that the blog keeps its personal spirit, since it strengthens the trustworthiness of the blog as a marketing channel. A blog is not supposed to communicate in an obviously selling purpose. What they write will rather more be recommendations for the reader. A blogger may sometimes be seen as opinion leaders and they possess the ability of influence a large number of people. The MeWe-generation makes an important target group for companies, since they are frequently influenced by blogs of fashion. Our conclusions also show us that openness and relations are important notions when discussing blogs as a marketing tool.</p>

<p> </p><p> </p><p>I föreliggande studie undersöktes ordförrådet (ordförståelse och benämning) hos 21 barn med hörselskada och 21 normalhörande barn i åldrarna 7-9 år, matchade till ålder, kön och bostadsort. Deltagarna delades även in i undergrupper med avseende på hörselskadans typ (ledningshinder, sensorineural skada samt kombinerad skada) och grad (lätt, måttlig, grav och döva/hörselskadade barn med CI) samt typ av skolform. Ordförståelse undersöktes med Peabody Picture Vocabulary Test III och benämning undersöktes med Word Finding Vocabulary Test. Som förväntat hade gruppen med hörselskada lägre resultat på båda testen, men endast benämningstestet visade en statistiskt signifikant gruppskillnad (<em>p </em>= 0,002 jämfört med <em>p </em>= 0,054 för ordförståelse). För benämningstestet hade barn med hörselskada i 7-års ålder ett signifikant lägre resultat jämfört med åldersmatchad kontrollgrupp, medan skillnaden inte var signifikant i de äldre åldersgrupperna (8 och 9 år). Typ, grad, kön eller skolform (hörselklass kontra integrerad skolform) hade ingen signifikant effekt på något av testen, men samband kan inte uteslutas pga relativt få barn i varje undergrupp i denna studie. Explorativ analys av individuella åldersekvivalenta resultat för benämningstestet indikerade följande: (a) majoriteten av de hörselskadade barnen låg inom den nedre halvan av normalresultatet; (b) två barn med cochleaimplantat hade särskilt låga resultat; (c) deltagare med lätt hörselskada tenderade att ha sämre resultat än deltagare med grav hörselskada, vilket kan tyda på otillräckligt stöd vid lätt skada; och (d) en deltagare med måttlig hörselskada hade lika högt resultat som det högsta resultatet i kontrollgruppen.</p><p> </p><p> </p> / <p>This study examined the receptive and expressive vocabulary in 21 children with hearing impairment and 21 children with normal hearing between the ages of 7-9. The groups were matched in regard to age, gender and home district. The material was divided into categories of hearing impairment based on type (conductive, sensorineural and combined hearing impairment), severity (mild, moderate, severe and children with profound deafness/hearing impairment with cochlear implant) and children in hard of hearing classes versus children integrated in ordinary classes. The tests used were Peabody Picture Vocabulary Test III (word comprehension) and Word Finding Vocabulary Test (word production). As expected, the group of children with impaired hearing achieved lower results on both tests. However, only the result on the word production test was significant for children with hearing impairment (<em>p </em>= 0,002 compared with <em>p </em>= 0,054 for comprehension). 7 years old children with hearing impairment reached a significantly lower result on the word production test compared with their peers with normal hearing, whereas the difference between the groups of 8 and 9 years old children was not significant. Type, severity, gender or school placement (hard of hearing classes versus ordinary classes) had no significant effect on neither word comprehension nor word production, but a correlation can not be out ruled because of a relatively low number of children in each subgroup. Explorative analyze of the individual age equivalent results for the word production test indicated: (a) the majority of children with hearing impairment performed within the lower half of the normal results; (b) two children with cochlear implants achieved a particularly low result; (c) participants with a mild hearing impairment tend to have a lower result than the participants with a severe hearing impairment, which might indicate insufficient support; and (d) one participant with moderate hearing impairment performed a result at the same level as the highest result in the control group.</p>