Women are warmer but no less assertive than men: gender and language on Facebook

Using a large social media dataset and open-vocabulary methods from computational linguistics, we explored differences in language use across gender, affiliation, and assertiveness. In Study 1, we analyzed topics (groups of semantically similar words) across 10 million messages from over 52,000 Facebook users. Most language differed little across gender. However, topics most associated with self-identified female participants included friends, family, and social life, whereas topics most associated with self-identified male participants included swearing, anger, discussion of objects instead of people, and the use of argumentative language. In Study 2, we plotted male- and female-linked language topics along two interpersonal dimensions prevalent in gender research: affiliation and assertiveness. In a sample of over 15,000 Facebook users, we found substantial gender differences in the use of affiliative language and slight differences in assertive language. Language used more by self-identified females was interpersonally warmer, more compassionate, polite, and—contrary to previous findings—slightly more assertive in their language use, whereas language used more by self-identified males was colder, more hostile, and impersonal. Computational linguistic analysis combined with methods to automatically label topics offer means for testing psychological theories unobtrusively at large scale.This work was supported by the Templeton Religion Trust

Living in the past, present, and future: measuring temporal orientation with language

OBJECTIVE: Temporal orientation refers to individual differences in the relative emphasis one places on the past, present, or future, and is related to academic, financial, and health outcomes. We propose and evaluate a method for automatically measuring temporal orientation through language expressed on social media. METHOD: Judges rated the temporal orientation of 4,302 social media messages. We trained a classifier based on these ratings, which could accurately predict the temporal orientation of new messages in a separate validation set (accuracy/mean sensitivity = .72; mean specificity = .77). We used the classifier to automatically classify 1.3 million messages written by 5,372 participants (50% female, aged 13-48). Finally, we tested whether individual differences in past, present, and future orientation differentially related to gender, age, Big Five personality, satisfaction with life, and depressive symptoms. RESULTS: Temporal orientations exhibit several expected correlations with age, gender, and Big Five personality. More future-oriented people were older, more likely to be female, more conscientious, less impulsive, less depressed, and more satisfied with life; present orientation showed the opposite pattern. CONCLUSION: Language-based assessments can complement and extend existing measures of temporal orientation, providing an alternative approach and additional insights into language and personality relationships. This article is protected by copyright. All rights reserved.Support for this article was provided by grant #63597 from the Robert Wood Johnson Foundation (M. E. P. Seligman, PI) and by a grant from the Templeton Religion Trust (M.E.P. Seligman, H. A. Schwartz, L. H. Ungar, co-PIs)

Personality, gender, and age in the language of social media: the open-vocabulary approach

We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses. Our analyses shed new light on psychosocial processes yielding results that are face valid (e.g., subjects living in high elevations talk about the mountains), tie in with other research (e.g., neurotic people disproportionately use the phrase ‘sick of’ and the word ‘depressed’), suggest new hypotheses (e.g., an active life implies emotional stability), and give detailed insights (males use the possessive ‘my’ when mentioning their ‘wife’ or ‘girlfriend’ more often than females use ‘my’ with ‘husband’ or 'boyfriend’). To date, this represents the largest study, by an order of magnitude, of language and personalit

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Triphasic Computed Tomography Enterography with Polyethylene Glycol to Detect Renal Cell Carcinoma Metastases to the Small Bowel

Enteroclysis was first used to diagnose small bowel obstruction in 1996. However, nasojejunal intubation required during enteroclysis causes discomfort to the patient. Triphasic computed tomography (CT) enterography, a noninvasive procedure that does not require intubation, was found to be an efficient method to diagnose small bowel lesions. We describe our experience of using triphasic CT enterography with polyethylene glycol (PEG) for diagnosing renal cell carcinoma (RCC) metastases to the small intestine. RCC can metastasize to many organs and can cause variable clinical presentations. We report the case of a 56-year-old man with RCC who had psoas muscle involvement and lung metastasis. The patient presented with melena and intermittent abdominal pain. Two conventional CT and small bowel series examinations had shown no obstructive lesion in the small intestine. However, triphasic CT enterography with PEG detected two enhanced masses suggestive of small bowel metastasis. The patient underwent laparotomy and segmental resection of the jejunum with primary anastomosis. Histologic examination was compatible with RCC. This is the first report where RCC metastasis to the small bowel was diagnosed using triphasic CT enterography. Our study emphasizes the importance of triphasic CT enterography in cases of obscure gastrointestinal bleeding, especially in patients suspected of having small bowel metastasis

The language of religious affiliation: social, emotional, and cognitive differences

Religious affiliation is an important identifying characteristic for many individuals and relates to numerous life outcomes including health, well-being, policy positions, and cognitive style. Using methods from computational linguistics, we examined language from 12,815 Facebook users in the United States and United Kingdom who indicated their religious affiliation. Religious individuals used more positive emotion words (β = .278, p < .0001) and social themes such as family (β = .242, p < .0001), while nonreligious people expressed more negative emotions like anger (β = −.427, p < .0001) and categories related to cognitive processes, like tentativeness (β = −.153, p < .0001). Nonreligious individuals also used more themes related to the body (β = −.265, p < .0001) and death (β = −.247, p < .0001). The findings offer directions for future research on religious affiliation, specifically in terms of social, emotional, and cognitive differences

RECIST revised: implications for the radiologist. A review article on the modified RECIST guideline

The purpose of this review article is to familiarize radiologists with the recently revised Response Evaluation Criteria in Solid Tumours (RECIST), used in many anticancer drug trials to assess response and progression rate. The most important modifications are: a reduction in the maximum number of target lesions from ten to five, with a maximum of two per organ, with a longest diameter of at least 10 mm; in lymph nodes (LNs) the short axis rather than the long axis should be measured, with normal LN measuring <10 mm, non-target LN ≥10 mm but <15 mm and target LN ≥15 mm; osteolytic lesions with a soft tissue component and cystic tumours may serve as target lesions; an additional requirement for progressive disease (PD) of target lesions is not only a ≥20% increase in the sum of the longest diameter (SLD) from the nadir but also a ≥5 mm absolute increase in the SLD (the other response categories of target lesion are unchanged); PD of non-target lesions can only be applied if the increase in non-target lesions is representative of change in overall tumour burden; detailed imaging guidelines. Alternative response criteria in patients with hepatocellular carcinoma and gastrointestinal stromal tumours are discussed