Applying linguistic methods to understanding smoking-related conversations on Twitter.

INTRODUCTION: Social media, such as Twitter, have become major channels of communication and commentary on popular culture, including conversations on our nation's leading addiction: tobacco. The current study examined Twitter conversations following two tobacco-related events in the media: (1) President Obama's doctor announcing that he had quit smoking and (2) the release of a photograph of Miley Cyrus (a former Disney child star) smoking a cigarette. With a focus on high-profile individuals whose actions can draw public attention, we aimed to characterise tobacco-related conversations as an example of tobacco-related public discourse and to present a novel methodology for studying social media. METHODS: Tweets were collected 11-13 November 2011 (President Obama) and 1-3 August 2011 (Miley Cyrus) and analysed for relative frequency of terms, a novel application of a linguistic methodology. RESULTS: The President Obama data set (N=2749 tweets) had conversations about him quitting tobacco as well as a preponderance of information on political activity, links to websites, racialised terms and mention of marijuana. Websites and terms about Obama's smoke-free status were most central to the conversation. In the Miley Cyrus data (N=4746 tweets), terms that occurred with the greatest relative frequency were positive, emotional and supportive of quitting (eg, love, and please), with words such as 'love' most central to the conversation. CONCLUSIONS: People are talking about tobacco-related issues on Twitter, and semantic network analysis can be used to characterise on-line conversations. Future interventions may be able to harness social media and major current events to raise awareness of smoking-related issues.

Explorations of lung cancer stigma for female long-term survivors.

Lung cancer is the leading cause of cancer death in women, accompanied by greater psychological distress than other cancers. There is minimal but increasing awareness of the impact of lung cancer stigma (LCS) on patient outcomes. LCS is associated with increased symptom burden and decreased quality of life. The purpose of this study was to explore the experience of female long-term lung cancer survivors in the context of LCS and examine how participants discursively adhere to or reject stigmatizing beliefs. Findings situated within Cataldo and colleagues' theoretical model include: (1) addiction and tobacco marketing as possible precursors for LCS, (2) the possible role of expert providers as LCS enhancers, (3) response of overlapping complicated identity shifts, (4) simultaneous rejection and assumption of LCS, and (5) information control via advocacy activities as a LCS mitigation response. These findings expand the current understanding of LCS, and call for future conceptual exploration and theoretical revision, particularly with respect to the possibility of interaction between relevant/related stigma(s) and LCS. As the number of women living with lung cancer increases, with longer survival times, the effect of LCS and other experiences of discrimination on patient outcomes could be substantial.

Automatic measurement of propositional idea density from part-of-speech tagging.

The Computerized Propositional Idea Density Rater (CPIDR, pronounced "spider") is a computer program that determines the propositional idea density (P-density) of an English text automatically on the basis of part-of-speech tags. The key idea is that propositions correspond roughly to verbs, adjectives, adverbs, prepositions, and conjunctions. After tagging the parts of speech using MontyLingua (Liu, 2004), CPIDR applies numerous rules to adjust the count, such as combining auxiliary verbs with the main verb. A "speech mode" is provided in which CPIDR rejects repetitions and a wider range of fillers. CPIDR is a user-friendly Windows .NET application distributed as open-source freeware under GPL. Tested against human raters, it agrees with the consensus of two human raters better than the team of five raters agree with each other [r(80) = .97 vs. r(10) = .82, respectively].

Does ketamine mimic aspects of schizophrenic speech?

Speech disturbances are well-known symptoms contributing to the diagnosis of schizophrenia. Subanesthetic doses of the N-methyl-D-aspartate (NMDA) antagonist ketamine have been reported to produce positive and negative symptoms and cognitive impairments consistent with those seen in schizophrenia. Insofar as this is true, it constitutes evidence that the NMDA system is involved in schizophrenia. It is therefore of interest to know whether ketamine produces speech disturbances like those of schizophrenia. Quantitative computer-aided analysis of apparently normal speech can detect clinically relevant changes and differences that are not noticeable to the human observer. Accordingly, in this study, speech samples were analysed for repetitiousness, idea density, and verb density using software developed by the authors. The samples came from two experiments, a within-subjects study of healthy volunteers given intravenous ketamine versus placebo, and a between-groups study of patients diagnosed with schizophrenia and comparable healthy controls.Our primary hypothesis was that in both schizophrenia and ketamine, repetitiousness would increase, since perserverative speech is a well-known symptom of schizophrenia. Our secondary hypotheses were that in both schizophrenia and ketamine, idea density and verb density would decrease as indicators of cognitive impairment. The primary hypothesis was confirmed in the schizophrenia experiment (between groups) and the ketamine experiment (within subjects). The secondary hypotheses were disconfirmed except that in the ketamine experiment, verb density was significantly lowered. Reduced use of verbs apparently reflects a cognitive impairment of a different type than repetitiousness, and further investigation is needed to determine whether this impairment occurs in psychosis.

Schizophrenia and the structure of language: the linguist's view.

Patients with schizophrenia often display unusual language impairments. This is a wide ranging critical review of the literature on language in schizophrenia since the 19th century. We survey schizophrenic language level by level, from phonetics through phonology, morphology, syntax, semantics, and pragmatics. There are at least two kinds of impairment (perhaps not fully distinct): thought disorder, or failure to maintain a discourse plan, and schizophasia, comprising various dysphasia-like impairments such as clanging, neologism, and unintelligible utterances. Thought disorder appears to be primarily a disruption of executive function and pragmatics, perhaps with impairment of the syntax-semantics interface; schizophasia involves disruption at other levels. Phonetics is also often abnormal (manifesting as flat intonation or unusual voice quality), but phonological structure, morphology, and syntax are normal or nearly so (some syntactic impairments have been demonstrated). Access to the lexicon is clearly impaired, manifesting as stilted speech, word approximation, and neologism. Clanging (glossomania) is straightforwardly explainable as distraction by self-monitoring. Recent research has begun to relate schizophrenia, which is partly genetic, to the genetic endowment that makes human language possible.