Browsing by Subject "Network analysis"

Now showing 1 - 6 of 6

Attention, search, and information diffusion : study of stock network dynamics and returns
(2014-08) Leung, Chung Man Alvin; Konana, Prabhudev C.; Agarwal, Ashish (Ph. D. in business administration)
There is growing literature on search behavior and using search for prediction of market share or macroeconomic indicators. This research explores investors' stock search behaviors and investigates whether there are patterns in stock returns using those for return prediction. Stock search behaviors may reveal common interest among investors. In the first study, we use graph theory to find investment habitats (or search clusters) formed by users who search common set of stocks frequently. We study stock returns of stocks within the clusters and across the clusters to provide theoretical arguments that drive returns among search clusters. In the second study, we analyze return comovement and cross-predictability among economically related stocks searched frequently by investors. As search requires a considerable amount of cognitive resources of investors, they only search a few stocks and pay high attention to them. According to attention theory, the speed of information diffusion is associated with the level of attention. Quick information diffusion allows investors to receive relevant information immediately and take instantaneous trading action. This immediate action may lead to correlated return comovement. Slow information diffusion creates latency between the occurrence of an event and the action of investors. The slower response may lead to cross-predictability. Making use of the discrepancy in information diffusion, we implement a trading strategy to establish arbitrage opportunities among stocks due to difference in user attention. This research enriches the growing IS literature on information search by (1) identifying new investment habitats based on user search behaviors, (2) showing that varying degrees of co-attention and economic linkages may lead to different speed of information diffusion (3) developing a stock forecasting model based on real-time co-attention intensity of a group economically linked stocks and (4) embarking a new research area on search attention in stock market. The methods in handling complex search data may also contribute to big data research.
Bridges in the global news arena : a network study of bridge blogs about China
(2012-08) Zheng, Nan, Ph. D.; Reese, Stephen D.; Chyi, Iris; Dahlby, Tracy; Lasorsa, Nick; Straubhaar, Joe
The concept of bridge blogs and their function to foster awareness and public discourse across the world was examined by content analysis and network analysis of 426 blog posts and 1026 links in 11 bridge blogs about China from 2009 to 2010. This study proposes a theoretical framework to examine how bridge blogs’ network characteristics are related to their communicative practices. Three variables were examined with respect to the network characteristics of bridge blogs. First, this study identifies different types of bridge blogs according to the distinctive sites with which they choose to link. Second, bridge blogs’ role as bridges is directly tested by the extent to which they connect between online information sources that are otherwise separated from one another. Third, this study examines bridge blogs’ level of centrality, which is based on the number links they receive from others in the network. For communicative practices, this study measures the type of links bridge blogs use as sources in their posts and the communicative frames used to structure the blog posts. Bridge blogs exhibit internal diversity in terms of what distinctive sites they linked to, level of betweenness and centrality. The finding supports the theoretical framework proposed in the study that bridge blogs’ three network characteristics are associated with their practices of communication as reflected in their use of links and content structure. Bridge blogs that play a crucial interconnecting role and are central points of reference in the network are more likely to bring Chinese content (as oppose to Western media coverage) and citizen voice (as oppose to professional media content) to English speaking readers. In addition, the translation of Chinese content, which contributes more to the flow of information and views from China to the outside world, is valued more by bridge blogs (than others?) that are important interconnecting actors in the network and positioned as central points of attention in the network. Further, a textual analysis further enriches the understanding of how the communicative frames are practiced by the bridge blogs, as illustrated in their references to four high profile news stories about China.
Community detection in network analysis: a survey
(2016-05) Zhang, Lingjia; Lin, Lizhen, Ph.D.; Keitt, Timothy
The existence of community structures in networks is not unusual, including in the domains of sociology, biology, and business, etc. The characteristic of the community structure is that nodes of the same community are highly similar while on the contrary, nodes across communities present low similarity. In academia, there is a surge in research efforts on community detection in network analysis, especially in developing statistically sound methodologies for exploring, modeling, and interpreting these kind of structures and relationships. This survey paper aims to provide a brief review of current applicable statistical methodologies and approaches in a comparative manner along with metrics for evaluating graph clustering results and application using R. At the end, we provide promising future research directions.
Mapping Cold War Cuba-Germanies Conceptual Frameworks through Castro Speech Data Base (1975-1990)
(2023-05-30) Rodríguez Alfonso, Adriana
For her fellowship, Adriana Rodríguez Alfonso created a dataset on Cuban-Germanies intellectual relations during the Cold War from the Fidel Castro’s speeches collections to visualize the main themes underscored as well as the semantic networks those ideas mobilized, in order to unveil the political and cultural imaginaries about both Germanies in the Caribbean island.
Taking a symptom level approach to adolescent depression
(2020-08-17) Mullarkey, Michael C.; Carlson, Caryn L.; Beevers, Christopher; Shumake, Jason; Marchetti, Igor; Yeager, David
Many individuals experience their first major depressive episode in adolescence (Merikangas et al., 2010), and even sub-clinical depressive symptoms in adolescents predict maladaptive outcomes (Bertha & Balázs, 2013). Still, sum scoring all of the items on a depression scale to determine severity, can be problematic psychometrically (Fried, van Borkulo, et al., 2016) and conceptually (Borsboom, 2008). Therefore, examining how individual depression symptoms relate to depression relevant outcomes appears to be an appropriate approach (Fried & Nesse, 2015b). However, no systematic evaluation of how individual depression symptoms relate to important outcomes has occurred in an adolescent sample. In Studies 1 and 2, I systematically evaluated which depressive symptoms may be more important during adolescence using network analysis (Borsboom & Cramer, 2013), a method that quantifies which symptoms are more central to a disorder (Valente, 2012). I found that self-hatred, sadness, loneliness, and pessimism were the most central symptoms in a large (N = 1,409), diverse (63.38% Non-Caucasian) sample of adolescents, and all assessed central symptoms replicated in a separate sample (N = 1,059) using a different measure of depression. Further, the more central a depression symptom was in the network the more variance it shared with life satisfaction (r = 0.59, 95% CI: 0.27, 0.76). In Study 3, I explicitly evaluated the replicability of strength centrality in cross-sectional adolescent depression networks using KL divergence and a pseudo R2 metric. Compared to a null model (R2 = 0) and a perfect replication (R2 = 1), cross-sectional network strength centrality replicated well (R2 = 0.80) across two samples (Ns = 1,159, 402) of non-selected adolescents. Using a novel application of bootstrapping, I found cross-sectional network strength centrality of adolescent depression in one sample predicts change over time centrality of adolescent depression in another sample (r = 0.81, 95% CI: 0.45, 0.92). My findings indicate more central adolescent depression symptoms as determined by network analysis, self-hatred, sadness, and loneliness, may be more important for depression related outcomes than more peripheral symptoms. Further investigating these central symptoms may more effectively advance our theoretical and clinical understanding of adolescent depression relative to investigating other symptoms.
Testing cold and hot cognitive control as moderators of a network of comorbid psychopathology symptoms in adolescence
(2019-08-19) Madole, James Wilson; Harden, Kathryn Paige
Comorbidity is pervasive across psychopathological symptoms, diagnoses, and domains. Network analysis is a method for investigating symptom-level associations that underlie comorbidity, particularly through bridge symptoms connecting diagnostic syndromes. We applied network analyses of comorbidity to data from a population-based sample of adolescents (n = 849). We implemented a method for assessing nonparametric moderation of psychopathology networks to evaluate differences in network structure across levels of intelligence and emotional control. Symptoms generally clustered by clinical diagnoses, but specific between-cluster bridge connections emerged. Internalizing symptoms demonstrated unique connections with aggression symptoms of interpersonal irritability, whereas externalizing symptoms showed more diffuse interconnections. Aggression symptoms identified as bridge nodes in the cross-sectional network were enriched for longitudinal associations with internalizing symptoms. Cross-domain connections did not significantly vary across intelligence but were weaker at lower emotional control. Our findings highlight transdiagnostic symptom relationships that may underlie co-occurrence of clinical diagnoses or higher-order factors of psychopathology