Partisan Provocation: The Role of Partisan News Use and Emotional Responses in Political Information Sharing in Social Media

Citizens increasingly rely on social media to consume and disseminate news and information about politics, but the factors that drive political information sharing on these sites are not well understood. This study focused on how online partisan news use influences political information sharing in part because of the distinct negative emotions it arouses in its audience. Using panel survey data collected during the 2012 U.S. presidential election, we found that use of proattitudinal partisan news online is associated with increased anger, but not anxiety, directed at the opposing party's presidential candidate and that anger subsequently facilitated information sharing about the election on social media. The results suggest partisan media may drive online information sharing by generating anger in its audience.     

Two theories of consciousness: Semantic pointer competition vs. information integration

Consciousness results from three mechanisms: representation by firing patterns in neural populations, binding of representations into more complex representations called semantic pointers, and competition among semantic pointers to capture the most important aspects of an organism’s current state. We contrast the semantic pointer competition (SPC) theory of consciousness with the hypothesis that consciousness is the capacity of a system to integrate information (IIT). We describe computer simulations to show that SPC surpasses IIT in providing better explanations of key aspects of consciousness: qualitative features, onset and cessation, shifts in experiences, differences in kinds across different organisms, unity and diversity, and storage and retrieval.     

Improving relational aggregated search from big data sources using stacked autoencoders

Relational aggregated search (RAS) is defined as a complementary set of approaches in which the relations between information nuggets are taken into account. From this viewpoint, the relational aggregated search should retrieve information nuggets and their relations, that are used to coherently assemble the final search result. Traditional approaches used for RAS are based on Information Extraction (IE) techniques and knowledge bases (ontologies, linked data) as the major sources for identifying and extracting useful relations between different results. However, with the big data collections stored on the web, the different results obtained from the different verticals for a given query are not homogeneous. Therefore, the challenge is to extract the different features related to each vertical result, and to recognize the various relationships between these results. In this paper, we propose a new solution based on a Deep Learning architecture, specifically, stacked autoencoders. This approach enables us to exploit the advantages of deep neural networks. Experimental results show that our model achieves good accuracy for 30 queries, and demonstrate that the use of stacked autoencoders for representation learning is more beneficial for clustering tasks and can considerably improve aggregated search results.     

From Context to Code: Information Transfer Constrains the Emergence of Graphic Codes

Humans commit information to graphic symbols for three basic reasons: as a memory aid, as a tool for thinking, and as a means of communication. Yet, despite the benefits of transmitting information graphically, we still know very little about the biases and constraints acting on the emergence of stable, powerful, and accurate graphic codes (such as writing). Using a reference game, where participants play as Messengers and Recipients, we experimentally manipulate the function of the task (communicative or non‐communicative) and investigate whether this shapes the emergence of stable, powerful, and accurate codes for both synchronous and asynchronous modes of information transfer. Only in the Dialogue condition, where Messenger and Recipient are two different persons communicating within the same time frame (i.e., synchronously), do we consistently observe the emergence of stable, powerful, and accurate graphic codes. Such codes are unnecessary for participants in Recall, where Messenger and Recipient are the same person transferring information within the same time frame, and they fail to emerge in Correspondence, where Messenger and Recipient are two different persons communicating across time frames (i.e., asynchronously). Lastly, in the Mnemonic condition, where Messenger and Recipient are the same person at different points in time, participants achieve high accuracy but with codes that are suboptimal in terms of power and stability. Our results suggest that the rarity and late arrival of stable, powerful, and accurate graphic codes in human history largely stems from strong constraints on information transfer. In particular, we suggest that these constraints limit a code's ability to reach an adequate tradeoff between information that needs to be explicitly encoded and information that needs to be inferred from context.     

“I Want to Know More!”: Children Are Sensitive to Explanation Quality When Exploring New Information

When someone encounters an explanation perceived as weak, this may lead to a feeling of deprivation or tension that can be resolved by engaging in additional learning. This study examined to what extent children respond to weak explanations by seeking additional learning opportunities. Seven‐ to ten‐year‐olds (N = 81) explored questions and explanations (circular or mechanistic) about 12 animals using a novel Android tablet application. After rating the quality of an initial explanation, children could request and receive additional information or return to the main menu to choose a new animal to explore. Consistent with past research, there were both developmental and IQ‐related differences in how children evaluated explanation quality. But across development, children were more likely to request additional information in response to circular explanations than mechanistic explanations. Importantly, children were also more likely to request additional information in direct response to explanations that they themselves had assigned low ratings, regardless of explanation type. In addition, there was significant variability in both children's explanation evaluation and their exploration, suggesting important directions for future research. The findings support the deprivation theory of curiosity and offer implications for education.     

时间对犯罪隐藏信息记忆的影响

记录模拟犯罪者和阅读报纸后对案件知情的无辜者接受隐藏信息测试时的皮肤电活动,探讨时间对犯罪隐藏信息记忆的影响。结果发现：(1)延迟条件下,模拟犯罪组的再认率和皮肤电活动变化显著高于知情无辜组,但两组在立即条件下无差异;(2)知情无辜组在延迟条件下的甄别率显著低于立即条件下,而模拟犯罪者在两种条件下无差异。结果表明,延迟测试比立即测试更容易区分模拟犯罪组和知情无辜组;犯罪甄别率在延迟条件下减少,但也减少了知情无辜者被判断为犯罪者的风险。     

Information‐Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory

A basic function of cognition is to detect regularities in sensory input to facilitate the prediction and recognition of future events. It has been proposed that these implicit expectations arise from an internal predictive coding model, based on knowledge acquired through processes such as statistical learning, but it is unclear how different types of statistical information affect listeners’ memory for auditory stimuli. We used a combination of behavioral and computational methods to investigate memory for non‐linguistic auditory sequences. Participants repeatedly heard tone sequences varying systematically in their information‐theoretic properties. Expectedness ratings of tones were collected during three listening sessions, and a recognition memory test was given after each session. Information‐theoretic measures of sequential predictability significantly influenced listeners’ expectedness ratings, and variations in these properties had a significant impact on memory performance. Predictable sequences yielded increasingly better memory performance with increasing exposure. Computational simulations using a probabilistic model of auditory expectation suggest that listeners dynamically formed a new, and increasingly accurate, implicit cognitive model of the information‐theoretic structure of the sequences throughout the experimental session.     

我军心理战理论研究热点问题概要

我军心理战研究兴起于20世纪80年代,虽然历时短,但发展迅速。特别是在心理战理论与实践中的一些热点问题上,已经形成了一些较为成熟的理论框架和思想观点。对心理战内涵和外延的界定上虽然有一定的争议,但已形成了较普遍地被认可的观点;对心理战效应和心理战运行机理,也已经形成比较明确的认识;对心理战地位作用普遍持肯定态度;对外军心理战理论与实践研究的剖析和学习借鉴,成为我军心理战发展的基础     

模拟网络信息主动增加特征的决策过程研究

与传统信息不同,网络信息具有可以主动增加的互动特征,本研究探讨这种特征对网络情境下决策加工过程的影响。通过改进的信息板技术追踪决策过程。实验一设置可否“主动增加信息”两种情境进行对照研究,发现引入主动增加功能后被试的搜索深度降低,先前知识的水平影响信息加工的模式;实验二设置可以连续要求增加信息的连续任务,比较不同的增加路径和选择阶段的影响,发现被试的搜索深度逐步降低,更多采用非补偿性的策略。两个实验均有超过半数的被试要求增加信息,连续任务有着32%的回头率,研究者推论在信息不断增加的情况下,被试的信息搜索行为更具选择性。     

The effects of bilingualism on toddlers' executive functioning

Bilingual children have been shown to outperform monolingual children on tasks measuring executive functioning skills. This advantage is usually attributed to bilinguals’ extensive practice in exercising selective attention and cognitive flexibility during language use because both languages are active when one of them is being used. We examined whether this advantage is observed in 24-month-olds who have had much less experience in language production. A battery of executive functioning tasks and the cognitive scale of the Bayley test were administered to 63 monolingual and bilingual children. Native bilingual children performed significantly better than monolingual children on the Stroop task, with no difference between groups on the other tasks, confirming the specificity of bilingual effects to conflict tasks reported in older children. These results demonstrate that bilingual advantages in executive control emerge at an age not previously shown.