AI dietician: Unveiling the accuracy of ChatGPT's nutritional estimations.

We investigate the accuracy and reliability of ChatGPT, an artificial intelligence model developed by OpenAI, in providing nutritional information for dietary planning and weight management. The results have a reasonable level of accuracy, with energy values having the highest level of conformity: 97% of the artificial intelligence values fall within a 40% difference from United States Department of Agriculture data. Additionally, ChatGPT displayed consistency in its provision of nutritional data, as indicated by relatively low coefficient of variation values for each nutrient. The artificial intelligence model also proved efficient in generating a daily meal plan within a specified caloric limit, with all the meals falling within a 30% bound of the United States Department of Agriculture's caloric values. These findings suggest that ChatGPT can provide reasonably accurate and consistent nutritional information. Further research is recommended to assess the model's performance across a broader range of foods and meals..

Testing ChatGPT's Capabilities for Social Media Content Analysis.

This letter explores the potential of artificial intelligence models, specifically ChatGPT, for content analysis, namely for categorizing social media posts. The primary focus is on Twitter posts with the hashtag #plasticsurgery. Through integrating Python with the OpenAI API, the study provides a designed prompt to categorize tweet content. Looking forward, the utilization of AI in content analysis presents promising opportunities for advancing understanding of complex social phenomena.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine Ratings, please refer to Table of Contents or online Instructions to Authors http://www.springer.com/00266 .

Leveraging ChatGPT for Human Behavior Assessment: Potential Implications for Mental Health Care.

This letter explores the capability of AI, specifically OpenAI's ChatGPT, in interpreting human behavior and its potential implications for mental health care. Data were collected from the Reddit forum "AmItheAsshole" (AITA) to assess the congruence between AI's verdict and the collective human opinion on this platform. AITA, with its vast range of interpersonal situations, provides rich insights into human behavioral evaluation and perception. Two key research questions were addressed: the degree of alignment between ChatGPT's judgment and collective verdicts of Redditors, and the consistency of ChatGPT in evaluating the same AITA post repeatedly. The results exhibited a promising level of agreement between ChatGPT and human verdicts. It also demonstrated high consistency across repeated evaluations of the same posts. These findings hint at the significant potential of AI in mental health care provision, underscoring the importance of continued research and development in this field.

Behind the ChatGPT Hype: Are Its Suggestions Contributing to Addiction?

ChatGPT has been a frequent topic of discussion lately. All over the Internet, from YouTube to blogs, there have been reports about how ChatGPT is able to plan people's daily activities, even for a whole month. However, what matters is what activities ChatGPT recommends. When ChatGPT was trained on a vast amount of data from the Internet, we wondered if it would suggest activities that can lead to addiction. In our test, not once did ChatGPT recommend an activity related to alcohol, drug use, or any other activity that can lead to addiction with serious health consequences. Suggestions seemed more like self-improvement posts on blogs than discussion forums where people might mention drinking in the evenings. Thus, if a person were to use ChatGPT as a personal lifestyle advisor, it does not appear on the basis of this test that ChatGPT would recommend activities that would be fundamentally detrimental to their health. However, more detailed long-term testing of similar tools is needed before recommendations for use in practice can be made.

Colombian political leaders on Twitter during the Covid-19 pandemic.

This study analyzes the use of Twitter by Colombian political elites during the Covid-19 pandemic, employing qualitative and quantitative methods and techniques. We collected Twitter data on the Colombian president, the mayor of Bogota, and all the members of the Congress of Colombia. We then analyzed qualitatively the content of the most popular tweets sent by President Iván Duque, Mayor Claudia López, and Gustavo Petro, the leader of the opposition. We also analyzed the growth in the number of their followers during the pandemic. We found that the most popular tweets from Colombian opposition politicians were often related to criticism of the government. López also informed her constituency about the state of the capital. President Duque's most popular tweets were primarily informative. During the pandemic, all three politicians gained a significant number of Twitter followers.

El objetivo de este artículo es analizar el uso de Twitter por parte de las élites políticas colombianas durante la pandemia de Covid­19. Para ello, empleamos métodos y técnicas cualitativas y cuantitativas. Recogimos datos de Twitter sobre el presidente colombiano, la alcaldesa de Bogotá y todos los miembros del Congreso de Colombia. A continuación, analizamos cualitativamente el contenido de los tuits más populares enviados por el presidente Duque, la alcaldesa López, y Petro, el líder de la oposición. También analizamos el crecimiento del número de sus seguidores durante la pandemia. Descubrimos que los tuits más populares de los políticos de la oposición colombiana solían estar relacionados con críticas al gobierno. López también informó a sus seguidores sobre el estado de la capital. Los tuits más populares del presidente Duque fueron principalmente informativos. Durante la pandemia, los tres políticos ganaron un número significativo de seguidores en Twitter.