Results 1 – 6 of 6 Naturaleza y lógica del capitalismo by Heilbroner, Robert L. and a great selection of Published by Siglo XXI Editores, México, D.F. (). Donor challenge: Your generous donation will be matched 2-to-1 right now. Your $5 becomes $15! Dear Internet Archive Supporter,. I ask only. El capitalismo del siglo XXITwenty-First Century Capitalism CARLOS SEGADE | 19 JUNIO Autor: ROBERT HEILBRONER.

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It consists of aroundtokens collected from profiles of Facebook users residing in South Tyrol, Italy. In conformity with the multilingual situation of the territory, the main languages of the corpus are German and Italian followed by English. The data has been manually anonymised and provides manually corrected part-of-speech tags for the Italian language texts and manually normalised data for German texts. Moreover, it is annotated with userprovided socio-demographic data among others L1, gender, age, education, and internet communication habits from a questionnaire, and linguistic annotations regarding CMC phenomena, languages and varieties.

The anonymised corpus is freely available for research purposes.

Robert Louis Heilbroner | Open Library

I dati sono stati manualmente anonimizzati e i testi in lingua italiana sono corredati da etichette manualmente corrette per le parti del discorso. The project initially focused on the Germanspeaking language group.

However, all information regarding the project, e. Hence, we attracted speakers of both Italian and German. Accordingly, the collected data is multilingual, with heilroner parts in German but with a substantial portion in Italianoftokens. The data was enriched with linguistic annotations on thread, text and token level including language-specific part-of-speech PoS and lemma information, normalisation, and language xzi.

Hence, it presents a continuation of Frey et al. We chose to collect data from Facebook as this SNS is well known in South Tyrol, hosts a wide variety of different communication settings, and is used over the whole territory by nearly all groups of the society.

Celli capitapismo PolonioBasile and NissimBurghardt et al. These issues heilbrober been solved by developing a Facebook application 2 that allowed for the gathering of all three sorts of data user consent, language data, questionnaire data at once.

In addition, the application was easy to share via Facebook which helped to promote the project and to reach many potential participants. Both entities were linked via randomised unique identifiers. A python interface provided access points to retrieve user and text data from the data base in a linked and structured format, and also allowed to rebuild the conversational structure of threads by linking successive text objects together.

This information can now be used to analyse turn-taking and language choices within threads 7. The used languages of a text were identified in a semi-automatic approach: Firstly, using the language identification tool langid.


The corpus was tokenized with the Twitter tokenizer ark-twokenize-py 9 and subsequently corrected manually for non-standard language tokenisation issues. Part-of-speech tagging and lemmatization: Corrected tokens were annotated with PoS tags and lemma information considering the predominant language of the text at hand. Subsequently, we manually corrected PoS annotations to handle bad tagging accuracy for social media texts. No manual correction was performed for these languages.

So far, we have manually normalised nonstandard language to word-by-word standard transcriptions only for German texts. We classified German texts as dialect, nondialect or unclassifiable texts applying a heuristic approach based on the normalisation. We have created a lexicon for untranslatable dialect words encountered during manual normalisation. The dialect lexicon was used to post-process out-of-vocabulary OOV tokens in the corpus. The most common OOV tokens that we manually classified as foreign language vocabulary have been annotated with information about their language origin.

Emoticons, emojis, mentions, hashtags, hyperlinks, and iterations of graphemes and punctuation marks were annotated automatically using regular expressions.

Topic of the text: In order to investigate context factors of language choice we annotated texts as either political or non-political according to a list of politicians, political parties and political terms.

Thread objects contain information about the used languages and the number of active interlocutors and recipients of a message as well as the time passed between two texts. If all interlocutors of a thread were participants of the project, the whole conversation is available.

The users could choose to provide either their Facebook wall communication status updates and commentstheir chat heilbrkner.

In the end, 50 people provided access to both types of data.

In total, the corpus consists of around thousand tokens that are distributed over the text categories status updates ,66 tokenscomments 94, tokens and chat messagestokens. The distribution of the languages is based on the language backgrounds of the participants and is comparable to the multilingual community of South Tyrol.

The following tables show the distribution of profiles, texts and tokens table 1 and text type table 2 by L1.

L1 Italian speakers stick more to their L1 compared to the German-speaking participants, who are characterized by a higher usage of L2 Italian. The comparison of L1 and L2 usage in status updates, comments and private messages c. Table 4 shows that the respective L1 is preferred in all messages types. We tried to address the demands of a multilingual corpus by providing language specific PoS tagging and by applying language independent annotations. We are aware of the fact that this is by no means sufficient to deal with linguistic research questions that exceed language boundaries.

Moreover, manual correction tasks occupied a significant part of the work on the corpus as automatic annotation e. The multilingual corpus is anonymised and annotated with socio-demographic data of users, language specific and for Italian manually corrected PoS tags, lemmas and linguistic annotations mainly related to used languages, varieties and multilingual phenomena.


The corpus is accessible for querying via ANNIS 12 or can be obtained as processable data for research purposes on http: How noisy social media text, how diffrnt social media sources. Valerio Basile and Malvina Nissim. Sentiment analysis on Italian tweets. Overcoming the limitations of short, unedited and idiomatic text. Language Resources and Evaluation47 1: Fabio Celli and Luca Polonio. Relationships between personality and interactions in facebook.

Lo standard tedesco in Alto Adige. Il segno e le lettere. What to do about bad language on the internet. Jennifer-Carmen Frey, Egon W. Stemle, and Aivars Glaznieks. Collecting language data of nonpublic social media profiles. Marco Lui and Timothy Baldwin. An off-the-shelf language identification tool. In Proceedings of the ACL system demonstrationspages 25— Association for Computational Lin.


Accurate language identification of twitter messages. Association for Computational Linguistics. Word level language identification in online multilingual communication.

A ripple down rules-based part-of-speech tagger. Probabilistic part-of-speech tagging using decision trees.

El capitalismo del siglo XXI – Robert Heilbroner – Google Books

In Proceedings of the international conference on new methods in language processingvolume 12, pages 44— Improvements in part-of-speech tagging with an application to German. A further word-level identification of languages could detect even more mixed-language content Nguyen and Dogruoz, You can suggest to your library or institution to subscribe to the program OpenEdition Freemium for books.

Feel free to give our address: We will be glad to provide it with information about Heilbroneg and its subscription offers. We will forward your request to your library as soon as possible. OpenEdition is a web platform for electronic publishing and academic communication in heillbroner humanities and social sciences. Desktop version Mobile version. Results per book Results per chapter. Lexical categories or frequency effects? A feedback from quantitati Search inside the book. Abstract Text Bibliography Notes Author s.

Association robetr Computational Lin- guistics. Notes 1 For further information see http: A further word-level identification of languages could detect even more mixed-language content Nguyen and Dogruoz, 12 http: Author s Jennifer-Carmen Frey. A feedback from quantitative methods The postal address of the institution is: A multilingual corpus of Facebook texts In: Available on heilbrkner Internet: A multilingual corpus of Facebook texts.

Frey, Jennifer-Carmen, et al. Corazza, Anna, et al. Accademia University Press, Corazza, Anna, et al.

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