Gazteak eta euskara sare sozialetan. Zer, nori, nork: euskarazko txio formal eta informalak sailkatuz eta konparatuz

[EU]Teknologia berrien etengabeko garapenak aldaketak eragin ditu gizakion arteko komunikazio moduetan. Honela, geroz eta ohikoagoa da sare sozialak eguneroko bizitzan erabiltzea, inolako mugarik gabeko komunikazioa ahalbidetuz. Komunikazio-esparru birtual honek hartueman publiko hauek jasotzeko aukera ematen du, Twitterren adibidez, testuan oinarritutako informazio mordoa edukiko da eskuragarri. Komunikazio-esparru berri honen sorrerak eta berau ustiatzeko aukerak ikerketa esparru berri bat irekitzeko aukera ematen du, ikerketa-teknika berriak beharko dituena. Aukera berri honi esker, euskararen etorkizunarekin erlazionatutako ikerketa burutzea izango da asmoa, hizkuntza honen erabilera Twitterren aztertuz. Ikerketa honetan arreta berezia jarriko da pertsona gazteetan, esparru berri hauetan nagusi izateaz gain, etorkizuna baitira. Horretarako euskal txiolariengan zentratuko da ikerketa, hauek bi taldeetan zatituz: gazte eta heldu. Behin banaketa burututa, talde bakoitzak ze gairi buruz hitz egiten duen eta zeinekin harremantzen diren azaleratzea izango da asmoa. Datu mordo hauek kudeatzeko lengoaia naturalaren prozesamenduko (NLP) teknikak erabiliko dira, ikerketa sozialerako konputazio zientzien teknikak aplikatuz.[EN]The continuous advance of new technologies has generated changes in the way of relating between humans. Therefore, it is increasingly common to use social networks in our day to day, allowing communication without limits. This new virtual space of communication allows to collect the ways of relating, on Twitter for example, we will have access to a lot of information based on text. The creation of this new communication space and the possibility of mining it allows the creation of a new field of research that needs new research techniques. Thanks to this new opportunity, the intention will be to carry out an investigation related to the future of Basque language, analyzing the use of this language on Twitter. In this research special attention will be placed on young people, since they are the majority in these new spaces as well as being the future. For this the research will focus on Twitter users who speak Basque, separating these into two groups: youth and adults. Once the separation is made, we will inquire about the topics they talk about or how the relationships in each group are given. To manage this massive data, natural language processing (NLP) techniques will be used, applying computer science techniques to social research

Euskarazko on-line artikuluetan aipatutako izendun entitate nabarmenen identifikazioa denbora errealean

Names referring to people, institutions, or places may be defined as named entities. Extracting named entities from news texts can help to identify the most commented topics talked about in news media. The main objective of this work is to identify in real-time those named entities that are most commented upon on Basque-language online media. In order to do so, we develop a system to automatically collect and annotate the named entities appearing in news written in Basque language. The annotation of named entities is performed using state-of-the-art deep learning models. Finally, the most frequent identified entities are published weekly in a Wikipedia page to display which entities do not currently have an article in the Basque Wikipedia.; Lan honen helburu nagusia, hedabideetako euskarazko edukian aipatzen diren izendun entitate nabarmenen identifikazioa da, identifikazioa denbora errealean eginez. Horretarako, euskaraz argitaratutako albisteetatik izendun entitateak automatikoki jaso eta etiketatzeko sistema garatu da, artearen egoerako Ikasketa Sakoneko ereduak erabiliz. Izendun entitateen identifikadoreari esker, denbora errealean jasotako albisteetako izendun entitateak etengabe identifikatu eta jasotzen dira, erregistro bat osatuz. Bukatzeko, identifikatutako izendun entitate nabarmenak astero publikatzen dira Wikipediako orri batean, Euskarazko Wikipedian artikulurik ez daukaten entitate nabarmenak erakusteko asmoz

Diagnostic efficacy of sentinel node biopsy in oral squamous cell carcinoma : cohort study and meta-analysis

Objectives: To evaluate the efficacy of sentinel node biopsy (SNB) in oral squamous cell carcinoma (OSCC). Design: A prospective study of a cohort of 25 consecutive patients with OSCC anatomopathological confirmation through biopsy, without oncological pre-treatment, in clinical stage T1-T4N0, of these 25 patients 14 were T1-T2N0. The absence of regional disease (N0) was determined by means of clinical exploration and cervical tomography (CT). To establish the overall sensitivity of the technique, a meta-analysis was carried out of 10 series published to February 2005 where SNB had been applied to head and neck cancer, adding our 14 T1-T2N0 cases, thus making a total of 260 patients. Results: Identification by SNB was accurate in 96% of the 25 cases, with a sensitivity of 66.7%. Analyzing only the T1-T2N0 cases (n=14), the accuracy was 100% with a sensitivity of 1 (CI 95%, 0.29-1.00). The overall sensitivity was 93%. The accuracy in identifying the sentinel node varied between 66% and 100%. The SN was identified in 251 of 260 cases, of those, 71 were true positive, 5 false negative and 175 true negative. The overall sensitivity was 93.4% (CI 95%, 85.3-97.8), with a specificity of 100% (CI 95%, 0.98-100). The weighted negative probability quotient was 0.176 (CI 0.103-0.301) and that of positive probability 24.75 (CI 95%, 10.8-56.71). The weighted diagnostic odds ratio was 183.71 (CI 95%, 59.36-568.56). If we accept that the prevalence of hidden regional disease is 30%, a negative sentinel node has 5% possibility of having hidden disease. Conclusions: Our data provide a certain degree of evidence that, due to its high sensitivity, the SNB procedure can be applied to the initial stages of OSCC

El modelo social europeo frente a la globalización

Jornada: El modelo social europeo frente a la globalización 18 de octubre 200