Seminar Topics Distribution & How to Find Literature Wiltrud Kessler Summer 2012
Seminar Topics Distribution & How to Find Literature Wiltrud Kessler Institut f¨ ur Maschinelle Sprachverarbeitung Universit¨ at Stuttgart Summer 2012 Organizational Stuff Topics Finding and Citing Literature Bibliography Outline Organizational Stuff Topics Finding and Citing Literature Bibliography Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 2 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Outline Organizational Stuff Topics Finding and Citing Literature Bibliography Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 3 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography The Plan for Today 1. All topics will be presented (in a very short way). 2. Distribution of topics (∀x∃y : student(x) ∧ topic(y ) → hasTopic(x, y ) ∧ (6 ∃z : hasTopic(a, z) ∧ hasTopic(b, z) ∧ a = b)). 3. Distribution of presentation dates: No Schein Dates in May / June preferred. Schein Dates in June / July preferred. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 4 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Course Evaluation I To get credit for this class, you need to chose a topic and present it in class. I The oral presentation should be around 30–45 minutes with a discussion afterwards (25 % of grade). I The written report should contain about X1 pages, a template will be provided (50 % of grade). I You need to participate actively in class, this includes reading all other papers (25 % of grade). For changes or further doubts please look at the evaluation page linked from the homepage. 1 depending on program Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 5 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Oral Presentation Length 30–45 minutes + discussion (shorter if no Schein). Template No template, it is not mandatory to have slides, feel free to use the blackboard or handouts. For slides LATEX Beamer2 is recommended. Submission Deadline is date of presentation, it is recommended to get feedback beforehand. Submissions will be managed in ILIAS. Format PDF. All seminar participants will read the main paper before the talk. Questions will be clarified in class. 2 https://bitbucket.org/rivanvx/beamer/wiki/Home – these slides have been created with LATEX Beamer. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 6 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Written Report (1) Length See next slide. Template Two-column conference paper format, a template will be available from the homepage for Word and LATEX. Submission A preliminary report has to be handed in a week before the talk. The final report has to be handed in a week after the talk. Submissions will be managed in ILIAS. Format Original document (DOC / TEX + figures) and PDF. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 7 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Written Report (2) B.Sc. 10–12 pages, focus on main paper. The final grade for the module will be an average of the grades in “Sentiment Analysis” and “Natural Language Generation”. Inf/M.Sc. elective 3 ECTS 10–12 pages, focus on main paper. M.Sc. elective 6 ECTS 15–20 pages, discuss related work, search for more literature, comment work in detail. M.Sc. concentration Please forget what I said last week! 5–10 pages, only main paper → Vorleistung (no grade). The questions in the oral exam will determine the grade for the concentration. No Schein No report. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 8 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Outline Organizational Stuff Topics Finding and Citing Literature Bibliography Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 9 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 1: Subjectivity Classification Subjective statements refer to the internal state of mind of a person and cannot be observed. In contrast, objective statements can be verified by observing and checking reality. It is sometimes useful for a sentiment analysis system to filter out objective language and predict sentiment based on subjective language only. Unfortunately, detecting subjectivity is also a complicated problem. References: [RW03], [WWH05] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 10 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 2: Subjectivity Word Sense Disambiguation Sentiment analysis often uses dictionaries that list the polarity of each word. However, many words have both subjective and objective senses. Subjective words used in an objective sense are a significant source of error in sentiment classification. Subjectivity word sense disambiguation tries to automatically determine which word instances in a corpus are being used with objective senses. References: [WM06], [AWM09], [AWCM11] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 11 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 3: Polarity Reversers To determine the polarity of an expression with only a lexicon of positive and negative words is often not sufficient, because many phenomena can influence the polarity. The most obvious example for such influences are “polarity reversers”, words that reverse the polarity of a sentiment word, e.g., “no” or “not”. An approach to tackle this problem is to assume the polarity of a word is known and classify each sentiment word as reversed or non-reversed according to its context. References: [ITRO08], [CC08], [WBRK10] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 12 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 4: Conditional Sentences Conditional sentences are sentences that describe implications or hypothtical situations and their consequences. Some conditional sentences directly express sentiment on a product, but many of them express a hypothetical situation, a wish or a general implication. References: [NLC09] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 13 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 5: Comparative Sentences A common way to express opinions is by comparing one entity with a different entity. There are different types of comparisons, direct comparisons of two entities, a comparison of the entity to a general standard and superlatives that set one entity above all others in the comparison set. Simply detecting comparative adverbs or adjectives is not sufficient, because it is possible for a sentence to contains a comparative word, although it is not a comparative sentence (”couldn’t agree with you more”) while on the other hand a comparative sentence does not necessarily have to include any comparative word (”no joy stick unlike the sony ericsson t60”). References: [JL06a], [JL06b], [GL08] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 14 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 6: Topic Models These papers present a framework for extracting ratable aspects of objects from online user reviews. A statistical model is used to discover topics in text and extract text snippets supporting the ratings of different aspects. References: [TM08b], [TM08a] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 15 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 7: Linguistic Features Many classifiers for the classification of sentiment polarity use only shallow features like bag-of-words. To enhance the accuracy of sentiment polarity classification, several features based on linguistic analysis and syntactic structures have been proposed. References: [DLP03], [Gam04], [MTO05] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 16 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Topic 8: Opinion Spam The term “opinion spam” refers to fictive reviews that have been written to mislead humans or automatic systems in their evaluation of the opinions about a product or a service. Fictive positive reviews are written to artificially improve the perceived opinion of a product or a service, fictive negative reviews are written to damage the reputation of a competitor or its products. References: [JL07], [JL08], [OCCH11] Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 17 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Themenverteilung Student Topic Date Program Topic 1 (Subjectivity) Topic 2 (Word Sense) Topic 3 (Reversers) Topic 4 (Conditionals) Topic 5 (Comparatives) Topic 6 (Topic Models) Topic 7 (Features) Topic 8 (Spam) Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 18 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Outline Organizational Stuff Topics Finding and Citing Literature Bibliography Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 19 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography How do I Find Literature? I Search for keywords. I Follow references in papers that you already have. I Look for papers that cite a paper that you already have (citation indexes). I References (!!) from Wikipedia. I Look for more papers from the same author (the last name in the list is usually the Professor). I It is not useful to only collect literature, you also have to read it. If there are too many papers to read all of them, it may be helpful to restrict the search to good conferences3 or journals4 . I Wikipedia or other webpages are not trustworthy sources. 3 4 ACL, COLING, EMNLP, NAACL, EACL Computational Linguistics Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 20 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography How do I get the Literature? I Offline (books etc.) I I I Unibibliothek, Landesbibliothek, Fernleihe. Verzeichnis lieferbarer B¨ ucher (VLB). Online I I I I I Wiltrud Kessler Scientific search engine: Google Scholar, CiteSeer, DBLP, . . . Citation indexes: Google Scholar, CiteSeer, Scirus, (ACM), (IEEE), . . . Digital publication lists (IEEE, ACM, Springer, ...) – often the publications there are only available to subscribers, the university library has some of these subscriptions (e.g. IEEE, ACM). Elektronische Zeitschriftendatenbank (EZB). Web pages of conferences or authors. Seminar Topics Distribution & How to Find Literature 21 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography How do I use Literature? – Citations/References I Whenever something is not your own idea, you need to specify where you got that idea from (6= Guttenberg). I This is done with a citation. I A citation is a reference (a shorthand name) to some source. There are different types of citatations: I I I I Wiltrud Kessler Verbatim citation (rare in NLP literature): ”Sentiment analysis is the task of identifying positive and negative opinions, emotions, and evaluations.” [WWH05] Author(s) of the paper as part of the sentence: [MTO05] use dependency sub-tree patterns for sentiment classification. Author(s) of the paper at the end of the sentence: Content words as well as function words have been used as polarity reversers [CC08]. Seminar Topics Distribution & How to Find Literature 22 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography How do I use Literature? – Bibliography I All the sources cited in your text must be listed at the end of your report in the bibliography. I The bibliography contains the citation shorthands used for reference in the report and the corresponding “long entry”, usually sorted alphabetically by first author. I The bibliography entry must contain all information needed to enable your reader to find your source again. I Main types of sources for us are conference papers, journal papers and books5 . I Necessary information: Author(s), title, year, conference proceedings OR journal name, pages (papers), publisher (books). 5 again, no web pages or Wikipedia. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 23 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography How do I use Literature? – Citation Styles I There are different citation styles. I Computer science people often cite using numbers (e.g. [123]) or using authors’ first letters and years (e.g. [CC08]). NLP people often use complete names and years, e.g. I I I Matsumoto et al. (2005) use dependency sub-tree patterns for sentiment classification. Content words as well as function words have been used as polarity reversers (Choi and Cardie, 2008). I It doesn’t matter which one you use as long as it is possible to find the citation in the bibliography. I Do not write the citations and the bibliography by hand, use automation – for LATEX there is bibtex, for Word/OpenOffice there are ways of referencing items in a text. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 24 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Outline Organizational Stuff Topics Finding and Citing Literature Bibliography Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 25 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Bibliography I [AWCM11] Cem Akkaya, Janyce Wiebe, Alexander Conrad, and Rada Mihalcea. Improving the impact of subjectivity word sense disambiguation on contextual opinion analysis. In Proceedings of CoNLL ’11, pages 87–96, 2011. [AWM09] Cem Akkaya, Janyce Wiebe, and Rada Mihalcea. Subjectivity word sense disambiguation. In Proceedings of EMNLP ’09, pages 190–199, 2009. [CC08] Yejin Choi and Claire Cardie. Learning with compositional semantics as structural inference for subsentential sentiment analysis. In Proceedings of EMNLP ’08, pages 793–801, 2008. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 26 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Bibliography II [DLP03] Kushal Dave, Steve Lawrence, and David M. Pennock. Mining the peanut gallery: opinion extraction and semantic classification of product reviews. In Proceedings of WWW ’03, pages 519–528, 2003. [Gam04] Michael Gamon. Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis. In Proceedings of COLING ’04, 2004. [GL08] Murthy Ganapathibhotla and Bing Liu. Mining opinions in comparative sentences. In Proceedings of COLING ’08, pages 241–248, 2008. [ITRO08] Daisuke Ikeda, Hiroya Takamura, Lev-Arie Ratinov, and Manabu Okumura. Learning to shift the polarity of words for sentiment classification. In Proceedings of IJCNLP ’08, pages 50–57, 2008. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 27 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Bibliography III [JL06a] Nitin Jindal and Bing Liu. Identifying comparative sentences in text documents. In Proceedings of SIGIR ’06, pages 244–251, 2006. [JL06b] Nitin Jindal and Bing Liu. Mining comparative sentences and relations. In Proceedings of AAAI ’06, pages 1331–1336, 2006. [JL07] Nitin Jindal and Bing Liu. Analyzing and detecting review spam. In Proceedings of ICDM ’07., pages 547–552, 2007. [JL08] Nitin Jindal and Bing Liu. Opinion spam and analysis. In Proceedings of WSDM ’08, pages 219–230, 2008. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 28 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Bibliography IV [MTO05] Shotaro Matsumoto, Hiroya Takamura, and Manabu Okumura. Sentiment classification using word sub-sequences and dependency sub-trees. In Proceedings of PAKDD ’05, pages 21–32. 2005. [NLC09] Ramanathan Narayanan, Bing Liu, and Alok Choudhary. Sentiment analysis of conditional sentences. In Proceedings of EMNLP ’09, pages 180–189, 2009. [OCCH11] Myle Ott, Yejin Choi, Claire Cardie, and Jeffrey T. Hancock. Finding deceptive opinion spam by any stretch of the imagination. In Proceedings of HLT ’11, pages 309–319, 2011. [RW03] Wiltrud Kessler Ellen Riloff and Janyce Wiebe. Learning extraction patterns for subjective expressions. In Proceedings of EMNLP ’03, pages 105–112, 2003. Seminar Topics Distribution & How to Find Literature 29 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Bibliography V [TM08a] Ivan Titov and Ryan McDonald. A joint model of text and aspect ratings for sentiment summarization. In Proceedings of ACL ’08, pages 308–316, 2008. [TM08b] Ivan Titov and Ryan McDonald. Modeling online reviews with multi-grain topic models. In Proceedings of WWW ’08, pages 111–120, 2008. [WBRK10] Michael Wiegand, Alexandra Balahur, Benjamin Roth, and Dietrich Klakow. A survey on the role of negation in sentiment analysis. In Proceedings of NeSp-NLP ’10, pages 60–68, 2010. [WM06] Wiltrud Kessler Janyce Wiebe and Rada Mihalcea. Word sense and subjectivity. In Proceedings of ACL ’06, pages 1065–1072, 2006. Seminar Topics Distribution & How to Find Literature 30 / 31 Organizational Stuff Topics Finding and Citing Literature Bibliography Bibliography VI [WWH05] Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of HLT ’05, pages 347–354, 2005. Wiltrud Kessler Seminar Topics Distribution & How to Find Literature 31 / 31
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