Competing for Attention in Online Reviews

Millions of web users engage in the online activities such as blogging, online forums, or online review systems to interact with people and to capture attention. This study tries to understand how online users compete for the scarce resource, attention, when participating in the online Web 2.0 activities. We develop a framework to capture the decision making process for online users to choose a right topic to post information and right content to post. Using book reviews from Amazon, we find that online reviewers do behave rationally in order to gain attention and to enhance their reputation. Our results suggest that experienced or top ranking reviewers are more likely to review relatively obscure books to avoid severe competition for attention in popular books. Moreover, top ranking reviewers usually post reviews earlier than low ranking reviewers as there are fewer reviews coexisting at the early stage to compete for attention. In terms of review ratings, we find that low ranking reviewers post more extreme ratings which distance themselves from the current average rating

A Multigeneration Diffusion Model for IT-Intensive Game Consoles

The video game industry has attracted more and more attention not only from technology giants such as Microsoft but also from software developers and private investors. Information technology dictates how game console producers compete in the marketplace. Intensive IT competition in each console generation has shifted the market balance. Competitors jockey to position themselves as the first-mover within a generation or to wait and enter the market with cheaper and more advanced technologies. To capture the characteristics of IT-intensive products, we propose a multigeneration diffusion model that captures both cannibalization and competition effects. We apply the model to analyze game console diffusion with real shipment data for three game consoles from two companies: Sony and Microsoft. We analyze two scenarios: one with only Sony¡¯s products, and one with both companies¡¯ products. We find that the cannibalization between Sony¡¯s products is minimal, and Microsoft maintains a strong competitive edge that has challenged Sony¡¯s market position. The results also explain how Sony has maintained its position as the market leader over the last two generations. This research sheds light on the nature of an IT-intensive game console competition between companies and generations

Quantification of Gender-related Stereotypes in Psychotherapy Sessions

Gender-related stereotypes and biases can have severe consequences in the medical domain, especially in mental health therapy. In this study, we analyzed 91 psychotherapy transcripts from the Alexander Street database to investigate whether gender-related stereotypes differ in the treatment of patients by male versus female therapists using natural language processing and statistical analyses. We built a lexicon of ten high-level categories that capture sentence-level attributes and represent gender-related stereotypes. Our results suggest significant statistical differences in categories such as active, negatives, positives, etc., during the treatment of female patients by male therapists as compared to female therapists. We built logistic regression models using the ten high-level lexical categories to predict the gender of the therapist. We also provide recommendations on how our analytical methods can be used, along with other advanced deep-learning methods, to detect and reduce gender-related stereotypes in psychotherapy sessions

The influence of different intensity of monsoon on typhoon precipitation: a comparative study of typhoons Soudelor and Maria

In this paper, multiple sets of reanalysis datasets are used to analyze the intensity of the Asian summer monsoon from 1979 to 2021. Typhoon Soudelor (No. 1513) and Typhoon Maria (No. 1808) were selected from the weak monsoon year 2015 and the strong monsoon year 2018, both of which were generated in the Northwest Pacific in July and made landfall in South China. The Weather Research and Forecasting Model (WRF) was used to simulate the two typhoons, starting 48 h prior to their landfall. The reasons for the differences in precipitation and how the monsoon affects typhoon precipitation in this process are analyzed from the aspects of monsoon background, ambient weather systems, typhoon thermodynamic structure, and water vapor conditions. The analysis shows that the circulation of Soudelor was stable and maintained for a long time. Despite existing in the background of a weak monsoon, the monsoon flow was able to reach the key area affecting typhoons and inject enough warm and moist flow to affect Soudelor. Combined with the analysis of typhoon structure, the strong water vapor transport of Soudelor and increased low-level convergence were conducive to the formation of typhoon-related rainstorms. The monsoon appeared to provide environmental conditions favorable for typhoon precipitation, resulting in a wide range of precipitation and heavy precipitation. Typhoon Maria developed and changed rapidly, moved rapidly, and the precipitation maintained itself for a relatively short time. The monsoon flow was not transported into Maria, resulting in insufficient water vapor inside Maria, which prevented the strengthening of typhoon precipitation. The precipitation of Maria mainly came from the dynamics of the typhoon itself and was not affected by the monsoon. In addition, this study defines an area on the southwest side of the typhoon moving with the center of the typhoon as the key area affecting typhoons. The characteristics of this area can be simply linked to typhoon precipitation, which can be considered an important research area for future analysis and prediction of typhoon precipitation

An Expression Tree Decoding Strategy for Mathematical Equation Generation

Generating mathematical equations from natural language requires an accurate understanding of the relations among math expressions. Existing approaches can be broadly categorized into token-level and expression-level generation. The former treats equations as a mathematical language, sequentially generating math tokens. Expression-level methods generate each expression one by one. However, each expression represents a solving step, and there naturally exist parallel or dependent relations between these steps, which are ignored by current sequential methods. Therefore, we integrate tree structure into the expression-level generation and advocate an expression tree decoding strategy. To generate a tree with expression as its node, we employ a layer-wise parallel decoding strategy: we decode multiple independent expressions (leaf nodes) in parallel at each layer and repeat parallel decoding layer by layer to sequentially generate these parent node expressions that depend on others. Besides, a bipartite matching algorithm is adopted to align multiple predictions with annotations for each layer. Experiments show our method outperforms other baselines, especially for these equations with complex structures.Comment: Accepted to EMNLP-2023, camera-ready versio