A Graph based Keyword Extraction from Twitter using Node and Edge Weight

Software fault localization technology aims to identify suspicious statements that cause software failures, which is crucial for ensuring software quality. Spectrum-based software fault location (SBFL) technology calculates the suspiciousness of each statement by analyzing the correlation between statement coverage information and execution results in test cases. SBFL has attracted increasing attention from scholars due to its high efficiency and scalability. However, existing SBFL studies have shown that a large number of statements share the same suspiciousness, which hinders software debuggers from quickly identifying the location of faulty statements. To address this challenge, we propose an SBFL model based on weighted association rule mining and complex networks: FL-WARMCN. The algorithm first uses Jaccard to measure the distance between passing and failing test cases, and applies it as the weight of passing test cases. Next, FL-WARMCN calculates the initial suspiciousness of each statement based on the program spectrum data. Then, the FL-WARMCN model utilizes a weighted association rule mining algorithm to obtain the correlation relationships between statements and models the network based on this. In the network, the suspiciousness of statements is used as node weights, and the correlation between statements is used as edge weights. We chose the eigenvector centrality that takes into account the degree centrality of statements and the importance of neighboring statements to calculate the importance of each statement, and used it as a weight to incorporate into the weighted suspiciousness calculation of the statement. Finally, we applied the FL-WARMCN model for experimental validation on the Defects4J dataset. The results showed that the model was significantly superior to other baselines. In addition, we analyzed the impact of different node and edge weights on model performance.

In many domains it is necessary to generate surrogate networks, e.g., for hypothesis testing of different properties of a network. Generating surrogate networks typically requires that different properties of the network are preserved, e.g., edges may not be added or deleted and edge weights may be restricted to certain intervals. In this paper we present an efficient property-preserving Markov chain Monte Carlo method termed CycleSampler for generating surrogate networks in which (1) edge weights are constrained to intervals and vertex strengths are preserved exactly, and (2) edge and vertex strengths are both constrained to intervals. These two types of constraints cover a wide variety of practical use cases. The method is applicable to both undirected and directed graphs. We empirically demonstrate the efficiency of the CycleSampler method on real-world data sets. We provide an implementation of CycleSampler in R, with parts implemented in C.

Given a large network, local community detection aims at finding the community that contains a set of query nodes and also maximizes (minimizes) a goodness metric. This problem has recently drawn intense research interest. Various goodness metrics have been proposed. However, most existing metrics tend to include irrelevant subgraphs in the detected local community. We refer to such irrelevant subgraphs as free riders. We systematically study the existing goodness metrics and provide theoretical explanations on why they may cause the free rider effect. We further develop a query biased node weighting scheme to reduce the free rider effect. In particular, each node is weighted by its proximity to the query node. We define a query biased density metric to integrate the edge and node weights. The query biased densest subgraph, which has the largest query biased density, will shift to the neighborhood of the query nodes after node weighting. We then formulate the query biased densest connected subgraph (QDC) problem, study its complexity, and provide efficient algorithms to solve it. We perform extensive experiments on a variety of real and synthetic networks to evaluate the effectiveness and efficiency of the proposed methods.

Graph-based semantic measures have been used to solve problems in several domains. They tend to compare semantic entities in order to estimate their similarity or relatedness. While semantic similarity is applicable to hierarchies or taxonomies, semantic relatedness is adapted to ontologies. In this work, we propose a novel semantic relatedness measure, named Rel Topic , within topic ontologies for topic labeling purposes. In contrast to traditional measures, which are dependent on textual resources, Rel Topic considers semantic properties of entities in ontologies. Thus, correlations of nodes and weights of nodes and edges are assessed. The pertinence of Rel Topic is evaluated for topic labeling of old press articles. For this purpose, a topic ontology representing the articles, named Topic-OPA, is derived from open knowledge graphs by applying a SPARQL-based automatic approach. A use-case is presented in the context of the old French newspaper Le Matin. The generated topics are evaluated using a dual evaluation approach with the help of human annotators. Our approach shows an agreement quite close to that shown by humans. The entire approach’s reuse is demonstrated for labeling a different context of articles, recent (modern) newspapers.

Mobile opportunistic networks (MONs) provide an efficient way for communication when there is no persistent connection between nodes. Compared to unicast routing schemes that have been extensively studied in MONs, multicast is an important communication technology in many realistic application scenarios that require to send data to multiple destination nodes, but it still lacks sufficient research. Most of the existing multicast routing schemes fail to consider the heterogeneity of nodes' capacities and resources. To address this issue, we propose a hierarchical multicast scheme in MONs by exploiting a backbone from a social network perspective. Firstly, we use the contact information between nodes to derive a weighted network contact graph. The weights of nodes and edges reflect the importance of nodes for relaying messages and the tightness of contacts between nodes, which are from a social network perspective. Secondly, we use the derived weighted graph to construct a backbone. Thirdly, we present a novel multicast algorithm by using the generated mobile backbone. Finally, we conduct extensive simulations based on real human contact datasets and the results show that our proposed social-aware backbone-based multicast routing scheme can effectively reduce the network overhead and energy consumption.

We consider the practical NP-complete problem of finding a minimum weight spanning tree with both edge weights and inner nodes weights. We present two polynomial time algorithms with approximation factors of 2.35 · ln n and 2Hn, respectively, where n is the number of nodes in the graph and Hn is the n-th Harmonic number. This nearly matches the lower bound of (l-\in )Hn, for any \in \ge 0. We also give an approximation algorithm with approximation factor \Delta - 1, where \Delta is the maximum degree of the graph. For metric spaces, we give a 3.105-approximation algorithm and show that an approximation factor of 1.463 is impossible unless {NP \subseteq DTIME[n^{O(\log longn)} ]}.

Purpose The technology determinism theory facilitated in assessing the impact of interactive radio and social network sites (SNSs) on development factors such as education, agriculture, health, and governance, by conducting an integrative and comprehensive literature review focusing on African countries. This paper aims to conduct this literature review to provide comprehensive empirical evidence on the impact of interactive radio and SNSs on development in Africa. Design/methodology/approach This study examined articles that were retrieved from online databases including EBSCOhost, Elsevier, Science Direct, SAGE Journals, Springer and Wiley Online Library. The keywords used included interactive radio, radio, development in Africa, SNS, agriculture, education, health, peace and governance. Search phrases were formulated using boolean operators “AND” and “OR.” Findings Study results revealed that interactive radio and SNSs improve knowledge among farmers and allow the dissemination of information on innovative agricultural techniques, which supports the adoption of sustainable practices. Interactive radio promotes political accountability because the strategies provide the voiceless and powerless communities with a platform to express themselves. This paper discovers that the incorporation of SNS with existing multimedia communication facilitates the dissemination of health-related information on illnesses such as Ebola, HIV, hypertension, diabetes and Polio, and interactive radio and SNS promote education among marginalized communities and under-served rural schools. Research limitations/implications The findings on the impact of interactive radio and SNSs do not represent all 54 countries in Africa. Although the studies included in this literature review were conducted in several countries such as South Africa, Nigeria, Somalia, Kenya, Malawi, Ghana, Tanzania, Uganda and Zambia, this limited the generalizability of the findings and recommendations. Also, the other potential limitation is that using the inclusion-exclusion criteria could have resulted in bias when selecting the studies to include in the review. Practical implications The paper might serve as a valuable source of information for students, academics and entrepreneurs where the impact of interactive radio and SNSs on agriculture, education, health and governance, which are core determinants of development in Africa, has been assessed for further case studies in this area. Social implications The use of interactive radio has helped in decreasing health issues caused by a deficiency in vitamin A among children in sub-Saharan Africa. Originality/value The development of sustainable and effective interactive radio programs is dependent on the collaboration of the core stakeholders such as governmental ministries, donor organizations and the mass communication sector. Numerous open sources on technology radio stations are available to employ social media managers to help in the application of knowledge.

We consider growing directed network models that aim at minimizing the weighted connection expenses while at the same time favoring other important network properties such as weighted local node degrees. We employed statistical mechanics methods to study the growth of directed networks under the principle of optimizing some objective function. By mapping the system to an Ising spin model, analytic results are derived for two such models, exhibiting diverse and interesting phase transition behaviors for general edge weight, inward and outward node weight distributions. In addition, the unexplored cases of negative node weights are also investigated. Analytic results for the phase diagrams are derived showing even richer phase transition behavior, such as first-order transition due to symmetry, second-order transitions with possible reentrance, and hybrid phase transitions. We further extend previously developed zero-temperature simulation algorithm for undirected networks to the present directed case and for negative node weights, and we can obtain the minimal cost connection configuration efficiently. All the theoretical results are explicitly verified by simulations. Possible applications and implications are also discussed.

KatzDriver: A network based method to cancer causal genes discovery in gene regulatory network

Social networks, functioning as core platforms for modern information dissemination, manifest distinctive user clustering behaviors and state transition mechanisms, thereby presenting new challenges to traditional information propagation models. Based on hypergraph theory, this paper augments the traditional SEIR model by introducing a novel hypernetwork information dissemination SSEIR model specifically designed for online social networks. This model accurately represents complex, multi-user, high-order interactions. It transforms the traditional single susceptible state () into active () and inactive () states. Additionally, it enhances traditional information dissemination mechanisms through reaction process strategies (RP strategies) and formulates refined differential dynamical equations, effectively simulating the dissemination and diffusion processes in online social networks. Employing mean field theory, this paper conducts a comprehensive theoretical derivation of the dissemination mechanisms within the SSEIR model. The effectiveness of the model in various network structures was verified through simulation experiments, and its practicality was further validated by its application on real network datasets. The results show that the SSEIR model excels in data fitting and illustrating the internal mechanisms of information dissemination within hypernetwork structures, further clarifying the dynamic evolutionary patterns of information dissemination in online social hypernetworks. This study not only enriches the theoretical framework of information dissemination but also provides a scientific theoretical foundation for practical applications such as news dissemination, public opinion management, and rumor monitoring in online social networks.

Summary Goals: Dry-on-vine (DOV) raisin grapes are cane-pruned to allow for cane severance, which initiates the DOV process, and to maximize yield potential. Yield components of Thompson Seedless raisin grapes, including the number of clusters per node, cluster and berry weight, and soluble solids per berry, have been shown to follow particular patterns with respect to node position, and this has informed pruning practice. However, DOV raisins in California are made from varieties that ripen earlier than Thompson Seedless, and they may have different fruiting characteristics. Therefore, we conducted a study to determine how the number of nodes per cane, and node position, affected yield components of DOV raisin grape varieties. Key findings: Basal nodes produced the fewest clusters due to poorer bud break and lower fruitfulness. Fiesta was the most fruitful variety, followed by Selma Pete, and then Thompson Seedless and DOVine. Cluster fresh weight increased whereas berry soluble solids (Brix) decreased with node position, regardless of cane length. Fruit from longer canes had less soluble solids (Brix) than the fruit from shorter canes, thus cane length did not usually affect total soluble solids (fruit fresh weight x soluble solids (Brix)) per cane. Fiesta produced more fresh fruit and total soluble solids per cane than other varieties. Impact and significance: Cane length had contrasting effects on fresh fruit weight and soluble solids, with shorter canes producing less fruit with higher soluble solids, whereas long canes produced more fruit of lower soluble solids. Harvested on the same date, these effects sufficiently countered each other such that canes of different lengths produced similar amounts of total soluble solids (sugar per cane) in two of three years. In California, where early maturity is preferred to ensure adequate drying time, shorter canes may be better than longer ones. However, if cane severance can be delayed to allow the berries to accumulate more sugar, which might be possible in other growing regions, or when drying emulsion may be used to hasten drying, longer canes could potentially increase raisin yield.

This study investigated information dissemination practices adopted by small and medium scale enterprises in Ebonyi State. Guided by one research question and a null hypothesis, the study employed a descriptive survey design. The population consisted of 2,433 registered SMEs, with a sample size of 344. A validated structured questionnaire was used for data collection. The Cronbach Alpha Reliability coefficient was 0.92. Descriptive statistics and t-test were used for data analysis. Findings revealed that SMEs use social media, YouTube, billboards, W hatsA pp, radio, and telev ision for information dissemination. No significant difference was found between male and female operators' ratings on information dissemination practices. Based on the findings of the study, it was recommended, among others, those small and medium scale enterprises operators should social media platforms for business information dissemination. Business education teachers should emphasize the benefits of information dissemination practices in promoting business activities.

The article explores the process of social and communicative dialogue as a form of discursive interaction in the public administration sphere. It was found out that the dialogueness acquires paradigmatic importance for public and administrative discourse as the plane of realization of political and managerial relations. Dialogic interaction through a systematic approach, based on globalization processes related to the modernization of public administration and the transformation (decentralization) of power relations, was actualized. Social dialogue as an institution of public administration, a certain form of social communication as well as an element of regulation and development of public relations was considered.In the author's sense, the concept of the dialogue was shown as a progressive transformation of power relations, which correlates with the paradigmatic foundations of the modern science of public administration, actualizing new forms of direct participation of citizens in the management of the public affairs. Peculiarities of dialogue between government authorities and civil society in Ukraine were found out as well as management aspects that need revitalization were highlighted.The purpose of the article is to analyze the features and implementation of social and communicative dialogue as a form of discursive interaction in the field of public administration.Conclusions. The successful formulation and implementation of public policy directly depends on the ability of public authorities to communicate effectively with the public, discuss alternative policy options and use public proposals to improve the quality of policy. In order to benefit from dialogue with the public, the authorities must be able to provide such dialogue. The most difficult and contradictory is the situation with the understanding of public authorities and citizens of their interdependence, and hence - the need to work together on the formation and implementation of public policy. That is why the competent answer to the need to improve the process of communication between government and society is the methodological possibilities of communicative philosophy and communication theory, aimed at changing the paradigm of thinking - from monologue to dialogue - and building a public deliberative process.Summarizing the results of the analysis of the category of social-communicative dialogue in the network, the main components are: subjects that are available in the context of the problem; the space of action provided by the world wide web as a whole and the specific platforms where communication takes place; time of action. The initiative of dialogue in the network arises as a reaction to objective reality. Social networks serve as a platform for public discussion and dissemination of information.

Vaccine hesitancy is gaining attention due to the increasing spread of the COVID-19 pandemic in Malaysia. Malaysia is a majority Muslim country and religion has a significant influence on the acceptance or rejection of vaccines. This is clearly seen through the disagreement over the halal status of vaccines. Social media has become a platform for discussion and dissemination of information and dis-information on vaccines. Thus, it has had a relatively significant influence on vaccine hesitancy among social media users. By analysing tweets from February 2020 to February 2021 using Twitter API, this paper highlights the discussion of COVID-19 vaccines’ halal status on Twitter. This study focuses on the analysis of vaccination reluctancy among the Twitter users in Malaysia and found that the most prevalent theme from the discussion is the constructed religious narratives to justify scientifically misleading and false claims concerning vaccination represented on social media. This finding also calls for a deeper understanding of society’s constructed knowledge concerning contemporary issues in the digital age on social media.

The weighted independent domination problem: Integer linear programming models and metaheuristic approaches