title = {Leave a {Comment}! {An} {In}-{Depth} {Analysis} of {User} {Comments} on {YouTube}},
abstract = {User comments are the most popular but also extremely controversial form of communication on YouTube. Their public image is very poor; users generally expect that most comments will be of little value or even in thorough- ly bad taste. Nevertheless, heaps of comments continue to be posted every day. We propose an explanation for this contradiction in user attitudes and behaviour based on a new comment classification approach which captures salient aspects of YouTube comments. We show that, based on our new classification, we are able to perform very fast lightweight semantic video analysis. In addition, our results indicate that users' video perceptions (Likes and Dislikes) are indeed in- fluenced by the dispersion of valuable and inferior comments.},
booktitle = {Wirtschaftsinformatik},
author = {Schultes, Peter and Dorner, Verena and Lehner, Franz},
year = {2013},
keywords = {Video content analysis}
}
@book{halte_les_2018,
address = {Limoges},
title = {Les émoticônes et des interjections dans le tchat},
title = {Comment {Relevance} {Classification} in {Facebook}},
isbn = {978-3-319-77116-8},
abstract = {Social posts and their comments are rich and interesting social data. In this study, we aim to classify comments as relevant or irrelevant to the content of their posts. Since the comments in social media are usually short, their bag-of-words (BoW) representations are highly sparse. We investigate four semantic vector representations for the relevance classification task. We investigate different types of large unlabeled data for learning the distributional representations. We also empirically demonstrate that expanding the input of the task to include the post text does not improve the classification performance over using only the comment text. We show that representing the comment in the post space is a cheap and good representation for comment relevance classification.},
booktitle = {Computational {Linguistics} and {Intelligent} {Text} {Processing}},
publisher = {Springer International Publishing},
author = {Liebeskind, Chaya and Liebeskind, Shmuel and HaCohen-Kerner, Yaakov},
editor = {Gelbukh, Alexander},
year = {2018},
pages = {241--254}
}
@misc{noauthor_exportcomments.com_2019,
title = {exportcomments.com},
url = {https://exportcomments.com/},
month = nov,
year = {2019}
}
@misc{ou-yang_newspaper3k:_2019,
title = {Newspaper3k: {Article} scraping \& curation},
url = {https://github.com/codelucas/newspaper/},
author = {Ou-Yang, Lucas},
year = {2019}
}
@inproceedings{mckinney_data_2010,
title = {Data {Structures} for {Statistical} {Computing} in {Python}},
booktitle = {Proceedings of the 9th {Python} in {Science} {Conference}},
author = {McKinney, Wes},
editor = {Walt, Stéfan van der and Millman, Jarrod},
year = {2010},
pages = {51 -- 56}
}
@incollection{baxter_discourse-analytic_2010,
title = {Discourse-analytic approaches to text and talk},
isbn = {978-0-8264-8993-7},
abstract = {This chapter explores the different ways in which discourse-analytic approaches reveal the ‘meaningfulness’ of text and talk. It reviews four diverse approaches to discourse analysis of particular value for current research in linguistics: Conversation Analysis (CA), Discourse Analysis (DA), Critical Discourse Analysis (CDA) and Feminist Post-structuralist Discourse Analysis (FPDA). Each approach is examined in terms of its background, motivation, key features, and possible strengths and limitations in relation to the field of linguistics. A key way to schematize discourse-analytic methodology is in terms of its relationship between microanalytical approaches, which examine the finer detail of linguistic interactions in transcripts, and macroanalytical approaches, which consider how broader social processes work through language (Heller, 2001). This chapter assesses whether there is a strength in a discourse-analytic approach that aligns itself exclusively with either a micro- or macrostrategy, or whether, as Heller suggests, the field needs to fi nd a way of ‘undoing’ the micro–macro dichotomy in order to produce richer, more complex insights within linguistic research.},
language = {English},
booktitle = {Research {Methods} in {Linguistics}},
booktitle = {In {Proceedings} of the {ACL} {Workshop} on {Effective} {Tools} and {Methodologies} for {Teaching} {Natural} {Language} {Processing} and {Computational} {Linguistics}. {Philadelphia}: {Association} for {Computational} {Linguistics}},
author = {Zeman, Daniel and Nivre, Joakim and Abrams, Mitchell and Aepli, Noëmi and Agić, Željko and Ahrenberg, Lars and Aleksandravičiūtė, Gabrielė and Antonsen, Lene and Aplonova, Katya and Aranzabe, Maria Jesus and Arutie, Gashaw and Asahara, Masayuki and Ateyah, Luma and Attia, Mohammed and Atutxa, Aitziber and Augustinus, Liesbeth and Badmaeva, Elena and Ballesteros, Miguel and Banerjee, Esha and Bank, Sebastian and Barbu Mititelu, Verginica and Basmov, Victoria and Batchelor, Colin and Bauer, John and Bellato, Sandra and Bengoetxea, Kepa and Berzak, Yevgeni and Bhat, Irshad Ahmad and Bhat, Riyaz Ahmad and Biagetti, Erica and Bick, Eckhard and Bielinskienė, Agnė and Blokland, Rogier and Bobicev, Victoria and Boizou, Loïc and Borges Völker, Emanuel and Börstell, Carl and Bosco, Cristina and Bouma, Gosse and Bowman, Sam and Boyd, Adriane and Brokaitė, Kristina and Burchardt, Aljoscha and Candito, Marie and Caron, Bernard and Caron, Gauthier and Cavalcanti, Tatiana and Cebiroğlu Eryiğit, Gülşen and Cecchini, Flavio Massimiliano and Celano, Giuseppe G. A. and Čéplö, Slavomír and Cetin, Savas and Chalub, Fabricio and Choi, Jinho and Cho, Yongseok and Chun, Jayeol and Cignarella, Alessandra T. and Cinková, Silvie and Collomb, Aurélie and Çöltekin, Çağrı and Connor, Miriam and Courtin, Marine and Davidson, Elizabeth and de Marneffe, Marie-Catherine and de Paiva, Valeria and de Souza, Elvis and Diaz de Ilarraza, Arantza and Dickerson, Carly and Dione, Bamba and Dirix, Peter and Dobrovoljc, Kaja and Dozat, Timothy and Droganova, Kira and Dwivedi, Puneet and Eckhoff, Hanne and Eli, Marhaba and Elkahky, Ali and Ephrem, Binyam and Erina, Olga and Erjavec, Tomaž and Etienne, Aline and Evelyn, Wograine and Farkas, Richárd and Fernandez Alcalde, Hector and Foster, Jennifer and Freitas, Cláudia and Fujita, Kazunori and Gajdošová, Katarína and Galbraith, Daniel and Garcia, Marcos and Gärdenfors, Moa and Garza, Sebastian and Gerdes, Kim and Ginter, Filip and Goenaga, Iakes and Gojenola, Koldo and Gökırmak, Memduh and Goldberg, Yoav and Gómez Guinovart, Xavier and González Saavedra, Berta and Griciūtė, Bernadeta and Grioni, Matias and Gr{\textbackslash}= uzītis, Normunds and Guillaume, Bruno and Guillot-Barbance, Céline and Habash, Nizar and Hajič, Jan and Hajič jr., Jan and Hämäläinen, Mika and Hà Mỹ, Linh and Han, Na-Rae and Harris, Kim and Haug, Dag and Heinecke, Johannes and Hennig, Felix and Hladká, Barbora and Hlaváčová, Jaroslava and Hociung, Florinel and Hohle, Petter and Hwang, Jena and Ikeda, Takumi and Ion, Radu and Irimia, Elena and Ishola, Ọlájídé and Jelínek, Tomáš and Johannsen, Anders and Jørgensen, Fredrik and Juutinen, Markus and Kaşıkara, Hüner and Kaasen, Andre and Kabaeva, Nadezhda and Kahane, Sylvain and Kanayama, Hiroshi and Kanerva, Jenna and Katz, Boris and Kayadelen, Tolga and Kenney, Jessica and Kettnerová, Václava and Kirchner, Jesse and Klementieva, Elena and Köhn, Arne and Kopacewicz, Kamil and Kotsyba, Natalia and Kovalevskaitė, Jolanta and Krek, Simon and Kwak, Sookyoung and Laippala, Veronika and Lambertino, Lorenzo and Lam, Lucia and Lando, Tatiana and Larasati, Septina Dian and Lavrentiev, Alexei and Lee, John and Lê H{\textbackslash}`ông, Phương and Lenci, Alessandro and Lertpradit, Saran and Leung, Herman and Li, Cheuk Ying and Li, Josie and Li, Keying and Lim, KyungTae and Liovina, Maria and Li, Yuan and Ljubešić, Nikola and Loginova, Olga and Lyashevskaya, Olga and Lynn, Teresa and Macketanz, Vivien and Makazhanov, Aibek and Mandl, Michael and Manning, Christopher and Manurung, Ruli and Mărănduc, Cătălina and Mareček, David and Marheinecke, Katrin and Martínez Alonso, Héctor and Martins, André and Mašek, Jan and Matsumoto, Yuji and McDonald, Ryan and McGuinness, Sarah and Mendonça, Gustavo and Miekka, Niko and Misirpashayeva, Margarita and Missilä, Anna and Mititelu, Cătălin and Mitrofan, Maria and Miyao, Yusuke and Montemagni, Simonetta and More, Amir and Moreno Romero, Laura and Mori, Keiko Sophie and Mo
year = {2019},
annote = {LINDAT/CLARIN digital library at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University}
abstract = {A French Lemmatizer in Python based on the LEFFF (Lexique des Formes Fléchies du Français / Lexicon of French inflected forms) is a large-scale morphological and syntactic lexicon for French. A lemmatizer retrurns the lemma or more simply the dictionary entry of a word, In French, the lemmatization of a verb returns this verb to the infinitive and for the other words, the lemmatization returns this word to the masculine singular.},
